OpenCode Integrations

Entire serves as a developer platform that seamlessly integrates with your Git workflow to document and retain AI agent sessions alongside your code, ensuring that the context of AI-driven development remains clear, easily searchable, and readily shareable. Whenever a commit is made, Entire’s command-line interface connects with Git to automatically capture detailed session data, such as transcripts, prompts, modified files, token usage, and tool interactions, creating versioned checkpoints that are directly linked to Git commits, which aids developers in comprehending the rationale and process behind AI-generated code. These checkpoints are treated as essential, long-lasting data stored in dedicated Git branches, allowing team members to examine AI interactions during code reviews, revisit decision-making contexts, trace development history, and enhance collaboration. Entire’s system guarantees that AI sessions do not merely exist transiently but become integral to the project's source context, making them searchable and understandable through tools designed to help teams rewind, evaluate, and share their workflows in the same manner they manage their code. This innovative approach not only fosters better communication among team members but also elevates the overall quality of the development process by maintaining a clear lineage of AI contributions.

Xiaomi MiMo-V2-Pro is an advanced AI foundation model engineered to support real-world agentic workloads and complex workflow orchestration. It serves as the central intelligence for agent systems, enabling seamless coordination of coding, search, and multi-step task execution. The model is built on a large-scale architecture with over a trillion parameters, supporting extended context lengths for handling complex scenarios. It demonstrates strong benchmark performance, particularly in coding and agent-based evaluations, placing it among top-tier global models. MiMo-V2-Pro is optimized for real-world usability, focusing on reliability, efficiency, and practical task completion rather than just theoretical performance. It features improved tool-calling accuracy and stability, making it suitable for integration into production environments. The model also excels in software engineering tasks, offering structured reasoning and high-quality code generation. With its ability to handle long-context interactions, it supports advanced workflows across development and automation use cases. Its API accessibility and competitive pricing make it attractive for developers and enterprises. Overall, MiMo-V2-Pro delivers a balance of scale, intelligence, and real-world performance for modern AI applications.

Maestri is a productivity and development platform designed specifically for macOS that facilitates the coordination of various AI coding agents, terminals, notes, and visual thinking tools within a limitless canvas, enabling developers to handle intricate workflows while preserving context. Rather than depending on conventional terminal tabs and disjointed tools, it offers a spatial interface where users can organize, connect, and observe multiple agents simultaneously, each executing tasks like coding, testing, or debugging concurrently. The platform fosters direct communication between agents, allowing them to delegate tasks, share outputs, and collaborate autonomously, all while providing users with complete oversight and control of the entire operation. Users can also engage in sketching and diagramming alongside the active agents, allowing for the mapping of architectures, workflows, and concepts in real time without the need to switch between different tools. This innovative workspace transforms the way developers interact with their projects, enhancing both creativity and efficiency.

OpenSpec is an open-source framework designed to enhance AI-assisted development through a structured, spec-driven approach. It provides a system for defining requirements before coding, ensuring alignment between developers and AI tools. The platform organizes work into clear artifacts, including proposals, specifications, design documents, and task checklists. It integrates with more than 20 AI coding assistants, making it compatible with a wide range of tools and workflows. OpenSpec promotes an iterative and flexible process, allowing teams to refine specifications as projects evolve. Its command-based interface enables users to propose features, implement changes, and archive completed work efficiently. By introducing structure, it reduces the unpredictability often associated with AI-generated code. The framework supports both individual developers and large teams, scaling across different project sizes. It also emphasizes context management to improve the accuracy and relevance of AI outputs. Ultimately, OpenSpec helps teams build software more reliably by combining human intent with AI execution in a structured workflow.

Cosyra offers a mobile-centric cloud development platform where users can access AI-driven coding utilities via a comprehensive Linux terminal right on their smartphones. Developers benefit from a suite of pre-installed tools including Claude Code, Codex CLI, OpenCode, and Gemini CLI, which can be easily activated by entering an API key and launching the terminal. It features an isolated Ubuntu environment equipped with key development resources like Node.js, Python, Git, tmux, and vim, along with 30 GB of persistent storage that retains data across sessions. Cosyra aims to emulate the functionality of a local development setup, enabling users to create, test, and oversee projects entirely through their mobile devices. The platform accommodates various workflows such as cloning repositories, reviewing pull requests, executing tests, and deploying code, all while maintaining a persistent session that can be paused and resumed without any disruption. By enhancing mobile productivity, Cosyra empowers developers to work flexibly and efficiently, breaking the limitations typically associated with traditional coding environments.

Mercury Edit 2 is a cutting-edge AI model from Inception Labs, part of the Mercury suite, specifically crafted for rapid reasoning, coding, and editing by employing a novel architecture distinctly different from typical large language models. It enhances the capabilities of Mercury 2, a diffusion-based model that generates and refines complete outputs simultaneously, rather than the conventional method of creating text one token at a time, which results in markedly improved speeds and more agile editing processes. Rather than functioning as a linear “typewriter,” this system operates as a dynamic editor, beginning with a rough draft and methodically enhancing it across multiple tokens simultaneously, facilitating real-time engagement and swift iterations in various tasks such as code editing, content creation, and agent-based workflows. This innovative framework achieves an impressive throughput of up to approximately 1,000 tokens per second, significantly outpacing traditional models while still upholding competitive reasoning abilities across various benchmarks. Its unique design not only transforms the way users interact with AI but also sets a new standard for performance in the field of artificial intelligence.

ui.sh is a terminal-centric toolkit aimed at empowering coding assistants to create high-quality user interfaces directly within a developer’s workflow, effectively transforming the terminal into a design engineer's platform. Specifically crafted for integration with AI coding tools like Claude Code, Cursor, Codex, and other similar agents, it enhances the UI output quality without the need for separate design applications or tedious manual adjustments. The toolkit is dedicated to elevating the standard of AI-generated interfaces by offering a systematic approach that focuses on layout, styling, and usability, thereby helping developers steer clear of poorly designed or inconsistent UI outcomes. By seamlessly fitting into terminal-based workflows, it enables developers to initiate UI creation, iterate on designs, and fine-tune components in real time, all within their current development setup. Developed by the team behind Tailwind CSS and Refactoring UI, the tool underscores the importance of delivering clean, production-ready design outputs, ensuring that developers have the resources they need to create visually appealing interfaces efficiently. This integration of design and coding not only streamlines the development process but also fosters creativity by allowing developers to experiment with their designs dynamically.

TypeUI is an open-source command-line tool crafted for agentic design, allowing developers to implement a cohesive and organized design framework throughout AI-generated code by creating and overseeing standardized files. Serving as a design layer for AI programming utilities, it guarantees that the interfaces generated by various agents adhere to uniform visual guidelines concerning typography, color, spacing, and component styling, irrespective of the model or provider utilized. This solution tackles a significant issue in AI-assisted software development, as outputs from tools like Claude Code, Cursor, Codex, or Gemini often exhibit notable inconsistencies in style. By introducing a versatile design blueprint, TypeUI promotes consistency across different projects. Users can effortlessly generate design systems through a straightforward CLI workflow, respond to guided prompts, access pre-existing “design skills” from a registry, or modify current configurations without the need for complete reconstruction. Ultimately, TypeUI empowers developers to focus more on functionality while maintaining aesthetic coherence in their applications.

LaReview is an innovative, open-source code review platform that emphasizes local-first functionality, aimed at turning pull requests and code diffs into organized, high-quality review processes that enhance comprehension while minimizing distractions. By accepting a GitHub or GitLab pull request or a raw diff as input, it employs AI coding agents to craft a structured review strategy that categorizes modifications based on workflows, potential risks, and developer intentions. This method enables developers to evaluate code in a thoughtful and systematic manner instead of merely browsing through files. LaReview adopts a reviewer-centric methodology, allowing engineers to effectively plan their assessments prior to providing feedback, and it seeks to generate constructive comments that offer substantial value rather than overwhelming reviewers with excessive low-impact remarks. The platform features AI-driven planning capabilities that scrutinize code similarly to a senior engineer, pinpointing potential issues and generating organized checklists, in addition to task-oriented review interfaces that coordinate tasks by logical sequences and underscore risks through tools such as file heatmaps. In doing so, LaReview not only streamlines the code review process but also fosters a culture of insightful and impactful feedback among development teams.

GPT-5.5 Pro is a next-generation AI model built for execution-heavy tasks across coding, research, business analysis, and scientific workflows. It can interpret complex instructions, break them into steps, and carry work through to completion using tools and automation. The model supports tasks such as generating documents, building applications, analyzing datasets, and navigating software environments. It is designed to operate across tools, enabling seamless workflows from idea to output. In addition, GPT-5.5 Pro integrates with workspace agents—customizable AI agents that automate recurring and multi-step processes across teams. These agents can handle tasks like lead research, reporting, and workflow automation, running independently or on schedules. Built with enterprise-grade safeguards, the model ensures secure and controlled automation. It helps organizations improve productivity by reducing manual effort and accelerating decision-making. GPT-5.5 Pro is ideal for teams looking to scale operations and handle complex workloads efficiently.

Your AI agents lack a true comprehension of your codebase; it's time to transition from mere text searching to genuine code understanding. Traditional AI coding agents often squander their context window on searching through files and making assumptions about the structure of the code. With Constellation, you can provide them with a comprehensive, team-wide knowledge graph of your codebase, which includes features like symbol search, dependency graphs, and impact analysis, all accessed through MCP. This innovative approach ensures that every token is utilized for reasoning rather than for the discovery process, leading to greater efficiency and more accurate code comprehension. By enhancing the understanding of the code, your team can work more cohesively and effectively.

Worktale is a developer tool focused on local-first principles that converts git history into a detailed and enduring account of a developer's creations, merging code activity monitoring with insights from AI within one cohesive platform. Functioning mainly as a lightweight command-line interface, it also offers an optional desktop version, meticulously scanning repositories to create a comprehensive work journal derived from commit metadata such as timestamps, messages, and line modifications, all while maintaining the privacy of the source code. The tool effortlessly records development activities using a post-commit hook or through batch imports, generating daily summaries that encapsulate progress, key decisions, and outputs, which can be modified and utilized for various purposes such as status updates, performance evaluations, or documentation. Additionally, it features visual dashboards that include streak tracking, contribution heatmaps, and historical analytics, empowering developers to identify and analyze productivity trends over time. This innovative approach not only enhances individual productivity but also fosters better collaboration within teams by providing clear insights into each member's contributions.

Subspace serves as an innovative workspace for AI-native agents, specifically crafted to aid developers and teams in the oversight, coordination, and collaboration with various coding agents within a cohesive environment that maintains context throughout different sessions. Rather than considering each interaction with AI as a separate event, this platform actively cultivates a persistent memory system that compresses every dialogue into structured insights, encompassing decisions, obstacles, and advancements, which are consistently refined to reflect an evolving state of the project. This collective memory is associated with the overall workspace instead of any specific tool, enabling diverse agents, such as Claude Code, Codex, and others, to seamlessly continue from where prior sessions concluded without the need for repetitive explanations or manual context shifts. With Subspace, users can integrate terminals, files, documentation, browser views, and git workflows into well-organized workspaces, allowing for the simultaneous operation of multiple agents while facilitating rapid transitions between different projects. Consequently, this comprehensive approach enhances productivity and collaboration, paving the way for more efficient development processes.

T3 Code serves as a streamlined web GUI tailored for coding agents like Codex, aiming to provide these agents with a more efficient work environment compared to traditional terminal setups. This tool is available for free, is open source, and is designed for quick installation, allowing users to connect it with existing harnesses they already utilize. Featuring a sleek, contemporary interface, T3 Code facilitates interaction with AI coding assistants via both web and desktop platforms, offering features such as session management, persistent state retention, thread oversight, and real-time collaboration capabilities. Developers can engage with coding agents through an easy-to-use chat interface, manage coding sessions across multiple projects, monitor changes thanks to integrated git support and checkpointing, and regulate access through distinct runtime modes like Full Access and Supervised. Moreover, T3 Code is built with flexibility in mind, allowing for modifications and customizations under an MIT license, which supports commercial use, and it utilizes TypeScript with robust end-to-end typing, all organized within a monorepo that encompasses desktop, web, server, and harness components, enhancing its versatility and utility for developers. This commitment to adaptability and user-friendliness makes T3 Code an appealing choice for developers seeking to improve their coding workflows.

Preloop serves as an open-source control plane designed for AI agents that perform tangible actions. It integrates a multi-layered security approach featuring an MCP firewall for managing tool access, an AI model gateway that ensures cost-effectiveness, safety, and accountability, along with policy-as-code that incorporates human oversight, all while providing runtime session visibility and audit trails—all within a self-hosted environment. Given the rapid capabilities of AI agents to deploy code, modify infrastructure, manage financial transactions, access production data, and incur model costs almost instantaneously, Preloop empowers teams to regulate agent activities, monitor expenditures, and determine which actions necessitate human consent. It is compatible with a variety of tools such as OpenClaw, Hermes, Claude Code, Codex CLI, Cursor, Gemini CLI, Windsurf, Cline, OpenCode, and any agents that adhere to MCP standards. Additionally, access rules can evaluate not only the tool names but also arguments and context, utilizing CEL expressions to establish detailed conditions. Furthermore, teams have the flexibility to initiate with observability features and progressively introduce approval and denial protocols without the need for SDKs or extensive modifications to existing applications, thus streamlining the implementation process. This comprehensive approach ensures that organizations remain in control of their AI agents' functionalities and impacts.

Multica is an innovative open-source project management platform designed for collaboration between human teams and AI agents, transforming coding agents into collaborative partners instead of merely being viewed as separate tools. This platform offers a unified workspace where both humans and AI can interact seamlessly; agents are capable of taking on tasks, providing updates, engaging in discussions, addressing obstacles, delivering code, and showcasing their presence along with profiles, avatars, and issue queues. Users can delegate tasks to agents as casually as they would to a fellow teammate, or they can initiate a chat to request issue drafting, inquiries, or to manage one-off tasks. Furthermore, Multica's shared context layer ensures that comments, attachments, reports, task histories, and workspace knowledge remain readily available to both agents and users, while the implementation of skills serves as comprehensive playbooks that empower all agents to utilize consistent definitions and operational guidelines. This integration not only enhances productivity but also fosters a more cohesive working relationship between humans and AI in the project environment.

AionUi serves as a desktop environment where AI agents reside directly on the user's computer, collaborating seamlessly on various daily tasks including coding, slide creation, file organization, data analysis, photo editing, report writing, academic paper drafting, and automating processes around the clock. Users have the flexibility to engage with a single agent, operate multiple agents simultaneously, delegate tasks to the most suitable assistant, or combine them within a cohesive workspace. This innovative platform automatically identifies and integrates with a variety of tools already available on the user's machine, including Claude Code, Codex, Gemini CLI, Aion CLI, OpenCode, OpenClaw, Goose, and many more, allowing for the efficient use of existing resources without the need for reinstallation. AionUi comes equipped with over twenty pre-built assistants designed for various applications such as presentations, Excel spreadsheets, financial modeling, document creation, academic writing, diagramming, UI/UX design, gaming, creative writing, project management, recruitment, setup processes, and complete autonomous workflows. Additionally, users have the option to develop custom assistants that are specifically designed to enhance their individual workflows, making the platform highly adaptable to different user needs. This level of customization ensures that every user can optimize their productivity while leveraging the power of AI.

Kimchi serves as a centralized platform designed for overseeing both SaaS and self-hosted AI models, enabling teams to deploy, route, optimize, and scale their LLM infrastructure seamlessly, all while maintaining their established developer workflows. This solution provides a unified control layer for managing AI coding agents, open-source models, commercial offerings, and internal inference, allowing organizations to blend cost-effective open-source solutions with premium providers like Claude, OpenAI, and Gemini when necessary. By prioritizing the reduction of LLM costs, Kimchi enhances the autonomy of development processes through efficient model routing, coding-focused inference, integration with multi-cloud platforms, support for multi-agent workflows, and the ability to interchange OSS and commercial models, all with minimal setup friction. Additionally, it facilitates the operation of the Kimchi coding agent across various teams, thereby broadening access to AI coding capabilities for engineering organizations while ensuring transparency in usage attribution, visibility into costs, and maintained operational governance. This comprehensive approach not only streamlines AI integration but also empowers teams to leverage the best resources available for their specific needs.

Vokal serves as a collaborative hub designed for teams and AI agents, enabling founders and product teams to manage agent tasks in a transparent environment where they can observe, evaluate, and repurpose important work. This platform ensures that human-agent collaborations have a centralized starting point, maintaining visibility and facilitating the reuse of contextual information, rather than relegating agent activities, assumptions, and decisions to isolated sessions across various tools like Claude Code, Codex, Cursor, and ChatGPT. By integrating channels, tasks, documents, files, applications, agents, memory, a Knowledge Base, identity, access rights, runtime, and event logs, Vokal empowers teams to keep their outputs synchronized, reviewed, controlled, and easily reusable. Agents operate within shared channels, which have designated owners, specified roles, clear instructions, reliable sources, defined statuses, permission scopes, application permissions, allocated memory, local project-file access, and observable activities. In addition, teams can utilize pre-defined roles tailored for engineering, product development, growth, customer support, operations, research, and other areas, or can opt to integrate their own local tools like Codex, Claude Code, and Hermes to suit their specific needs. This flexibility not only enhances collaboration but also fosters a more efficient workflow among team members and AI agents alike.

Graphify serves as an innovative open source knowledge graph engine that converts diverse inputs such as code, documentation, research papers, meetings, images, browser tabs, and commits into a single, navigable graph with full recall capabilities. Designed to function as a persistent memory for AI coding assistants, it empowers tools like Claude Code, Codex, OpenCode, Cursor, Gemini CLI, GitHub Copilot CLI, Aider, Factory Droid, Kimi Code, Kiro, Pi, and Google Antigravity with a queryable grasp of a project, thereby eliminating the need for them to continuously search through files. Users can direct Graphify to any directory, where it generates an initial corpus through AST extraction, semantic analysis, and Leiden clustering, effectively converting an entire codebase or document collection into a comprehensive graph in a single operation. Unlike traditional RAG pipelines that require re-embedding for every modification, Graphify sustains a dynamic graph that only updates the affected nodes and edges when files are altered, allowing the remainder of the corpus to remain stable even at an enterprise scale. This capability not only enhances efficiency but also facilitates seamless collaboration among various AI tools, significantly improving the overall workflow for developers and researchers alike.

MemPalace is a storage and retrieval system that prioritizes local-first principles for AI workflows, ensuring that users retain control over their conversations while providing AI with a form of memory. Instead of summarizing dialogues, it stores them in their entirety and organizes this information into a navigable "palace" structure, drawing inspiration from the classical memory palace method. Users can categorize conversations into designated wings based on individuals, projects, or themes, while utilizing rooms and drawers to facilitate easy access and retrieval of information. This system is tailored for those who value ownership of their words, featuring local-first storage, no telemetry, and a strong emphasis on privacy by keeping all memory on the user's device. Additionally, MemPalace enhances AI functionalities through MCP tooling, which includes features for reading and writing within the palace, performing knowledge-graph operations, navigating across wings, managing drawers, and maintaining agent diaries. Ultimately, MemPalace serves as a bridge between user agency and AI memory, creating a seamless experience that respects personal privacy.

OpenViking is an open-source context database tailored for AI agents, utilizing a file-system architecture to streamline the management of memories, resources, and skills. Rather than viewing context as disjointed pieces in a fragmented vector store, OpenViking consolidates agent context into a virtual file system through the viking protocol, allowing agents to effectively store, navigate, retrieve, and observe the necessary information. This system is designed to alleviate the burdens of manual context management for developers, offering agents a simplified interaction model akin to file operations. Furthermore, OpenViking facilitates hierarchical context loading, semantic and recursive retrieval, session management, metrics tracking, and observability, enabling AI agents to efficiently access pertinent information without overwhelming prompts. By adopting this approach, developers can enhance the efficiency and effectiveness of their AI systems.

Hindsight is an innovative memory framework designed to enhance AI agents by enabling them to learn progressively rather than resetting their knowledge with each new interaction. Unlike traditional memory systems that primarily focus on recalling past conversations, Hindsight prioritizes the learning process, equipping agents with a persistent long-term memory through advanced biomimetic data structures. This functionality allows AI agents to keep track of essential facts, access relevant context, and engage in reflective reasoning based on their experiences. Hindsight is particularly beneficial for agents that require a deep understanding of user identities, previous discussions, evolving preferences, decision-making histories, and necessary behavioral adjustments across different sessions. To achieve this, it incorporates three fundamental operations: retain, which captures new information; recall, which accesses appropriate memories when required; and reflect, which aids agents in synthesizing observations, developing mental frameworks, and gaining insights from earlier interactions. By implementing these features, Hindsight ensures a more personalized and context-aware experience for users.

claude-mem serves as an offline-first cloud memory solution for AI agents, centered around an open source engine along with a cloud synchronization layer that connects agent memories universally through a single private MCP link. Its design ensures that coding agents and AI assistants do not begin from scratch in each session, regardless of the machine or editor in use. As agents work, claude-mem efficiently records notes that encapsulate decisions, solutions, obstacles, environmental insights, architectural choices, and a variety of structured observations within a temporal database. The CMEM Cloud then replicates this local memory through a private Model Context Protocol endpoint, enabling any compatible agent or integrated development environment to access and modify the same memory across various platforms such as Claude Code, Cursor, Windsurf, OpenCode, Codex CLI, Gemini CLI, and VS Code. Operating primarily in a local setting, it maintains functionality whether or not a network connection is available, and ensures that memory is kept in sync whenever cloud access is present. This innovative approach enhances the continuity of AI interactions, facilitating a smoother experience for developers and users alike.

CMEM Cloud serves as the synchronization layer for claude-mem, designed to connect AI agent memory universally via a single private MCP link. The open-source engine, claude-mem, records notes while an agent performs tasks, while CMEM Cloud replicates that local memory, enabling agents to access it seamlessly across different sessions, devices, editors, and any MCP-compatible client. This innovative system eliminates the need for users to repetitively clarify context, copy previous notes, or start from scratch by automatically logging decisions, bug fixes, dead ends, environmental observations, architectural decisions, and other structured insights as the agent operates. These valuable insights are preserved in a temporal database, allowing for meaning-based searches through vector recall, and are accessible via a private MCP endpoint that any compatible agent can utilize for reading and writing. The process initiates with the installation of the local engine, followed by allowing a secondary model to generate structured notes independently, syncing the local database with CMEM Cloud, and finally enabling memory recall from any location. This approach not only enhances efficiency but also fosters a more collaborative environment among agents by sharing insights effortlessly.

PageAI is the best AI website builder, ranked as the top AI website generator by multiple publications. It's powered by the latest state of the art AI models that transform a simple prompt into a fully functional, production-ready website within minutes. It employs specialized AI agents to meticulously plan, research, design, and code each individual page, generating wireframes, selecting themes, creating visual assets, and producing professional-quality copy, ultimately delivering clean and maintainable code in Next.js + TypeScript built on Shadcn UI and Tailwind CSS. Users have access to a drag-and-drop editor with live preview capabilities, enabling them to personalize various elements such as themes, fonts, text, images, icons, and the arrangement of sections according to their preferences. Each website is designed with SEO best practices in mind, equipped with essential features like meta tags, JSON-LD, canonical URLs, sitemaps, RSS feeds, dynamic social images, favicons, dark mode support, and a built-in MDX blog that includes search functionality, tags, and multiple layout options, as well as terms and privacy pages. With a simple one-click deployment to Vercel or the option to download the complete codebase, users enjoy a hassle-free experience. There are no subscription fees or long-term commitments involved; you pay only once for each website, and the code is yours to keep indefinitely, with unlimited edits included, offering both flexibility and ownership. Additionally, this model allows users to focus on their creativity without worrying about ongoing costs or restrictions.

Laguna XS.2 represents Poolside’s innovative open-weight coding model, distinguished as the lightest and quickest member of the Laguna series. This model features a total of 33 billion parameters in a Mixture of Experts setup, with 3 billion parameters activated, and has been meticulously trained in-house using 30 trillion tokens. As the latest generation model accessible to the public, it embodies a second-generation architecture and marks Poolside’s inaugural open-weight offering, drawing from insights gained during the training of Laguna M.1 with synthetic data and reinforcement learning techniques. Specifically designed to enhance agentic coding workflows, Laguna XS.2 excels in coding, acting, and rapidly iterating, particularly within Poolside’s coding agent environment. This model is particularly advantageous for developers and teams seeking a lightweight, efficient coding solution rather than a more cumbersome frontier system. Released under the permissive Apache 2.0 license, it empowers the community to assess, fine-tune, quantize, and build upon its weights, fostering a collaborative development atmosphere. In essence, Laguna XS.2 not only provides a robust platform for agentic coding but also encourages innovation and experimentation among its users.

Laguna M.1 stands out as Poolside's most proficient model for agentic coding, meticulously developed in-house specifically for enhancing software development workflows. This model features a total of 225 billion parameters, utilizing a Mixture of Experts architecture with 23 billion activated parameters, and has been trained entirely within the organization on a dataset consisting of 30 trillion tokens, leveraging the power of 6,144 interconnected NVIDIA H200 GPUs. Poolside undertook the task of training Laguna M.1 from the ground up, employing its proprietary data, dedicated training codebase, and an asynchronous on-policy reinforcement learning approach within its agent framework, all tailored for agentic coding applications. The design of the model ensures optimal performance within Poolside's coding agent, enabling it to effectively reason through software tasks, interact with various tools, edit code, execute tests, and facilitate extended autonomous development sessions. Specifically crafted for developers and teams tackling intricate coding challenges, Laguna M.1 offers enhanced capabilities in reasoning, architectural comprehension, terminal operations, and multi-step execution, surpassing what lighter models can achieve. Ultimately, its robust feature set positions it as an essential asset for those engaged in demanding software projects.

Citlyze is a platform that enhances AI visibility by analyzing how various AI answer engines, such as ChatGPT, Gemini, Perplexity, and Grok, represent, reference, and rank your brand. You can consistently monitor the buyer inquiries that are significant to your business, check if your brand receives mentions or endorsements, and evaluate your visibility relative to your competitors over time. With citation tracking, you can discover which URLs and domains AI engines reference when generating answers—distinguishing between citations from your own site and those from competitors—thus identifying which sources hold persuasive power. The platform also tracks which bots, like GPTBot, ClaudeBot, and PerplexityBot, are accessing your website, while GEO audits ensure that answer engines can properly access and interpret your content. Content agents utilize visibility gaps to create reviewable article drafts that are rooted in the references AI systems already utilize. Progress can be shared through scheduled reports sent via email, Slack, or Teams, and you also have the option for CSV exports and a read-only API. Designed specifically for marketing and SEO teams, Citlyze is also ideal for agencies that handle AI search visibility across various client brands, making it a comprehensive tool for enhancing online presence. Ultimately, Citlyze empowers brands to optimize their visibility in an increasingly AI-driven landscape.

AgentKey seamlessly integrates your AI agents with external data sources using a single key, enabling them to perform real tasks effectively. While your agent may possess the knowledge to undertake specific actions, it requires access to the appropriate APIs and services to execute them successfully. AgentKey streamlines this process, allowing the agent to conduct extensive searches, extract information from web pages, gather social insights, and incorporate context from various sectors like finance, ecommerce, business, crypto, and on-chain data in one comprehensive operation. Designed to work with platforms such as Claude Code, Codex, Cursor, Windsurf, Gemini CLI, OpenClaw, Hermes, Antigravity, and Warp, as well as any system that is compatible with MCP or Skills files, AgentKey equips agents with the ability to access a wealth of information without the hassle of managing multiple provider dashboards. The search capabilities encompass services like Brave Search, Tavily, Serper, Perplexity, Parallel, and Exa, while scraping functionalities leverage tools like Firecrawl, Jina, and Bright Data to convert web content into actionable insights. This innovative solution not only enhances efficiency but also empowers agents to deliver more informed and context-rich outcomes in their operations.

Unabyss serves as a comprehensive context layer for AI applications, seamlessly integrating and maintaining live, structured context across all AI interactions a user engages with. It aggregates data from various daily work platforms, including Slack, Gmail, Notion, Google Calendar, GitHub, Linear, Google Drive, and meeting applications, while automatically extracting, organizing, tagging, and updating that context in real time. Rather than confining knowledge within a single chatbot or relying on outdated context files, Unabyss empowers tools such as Claude, ChatGPT, Cursor, Codex, Gemini, Perplexity, OpenCode, VS Code, and OpenClaw to draw from a unified knowledge base. Each AI can access only the pertinent context based on criteria like topic, source, sensitivity, project, and account, ensuring that users are not burdened with the need to repeatedly communicate their roles, preferences, decisions, clients, repositories, or current priorities. This innovative approach enhances productivity and collaboration, allowing users to focus on their tasks without the hassle of redundant explanations.

port22 allows you to carry your coding agents with you, making it easy to run the agent from your iPhone while overseeing its actions through a live transcript. You can interact with Claude Code, Codex, or OpenCode from virtually anywhere, approving actions as the agent operates. Instead of initiating a new session, it seamlessly connects to the existing one running in your terminal, ensuring you can maintain continuity with your work from your desk. As the agent thinks, edits, and executes commands, every token is streamed directly to your phone, and you receive push notifications when it requires your input or has completed a task. The current status of the session is readily accessible via the Dynamic Island and lock screen, enabling you to monitor every ongoing process without the hassle of opening the app repeatedly. Additionally, port22 functions over your local network while at your desk, and when you're on the go, it effortlessly transitions to a secure, end-to-end encrypted relay, allowing you to keep the same session active over cellular data as well. This innovative approach ensures that your workflow remains uninterrupted, regardless of your location.

bb is an innovative, local-first IDE that allows for extensive customization while interacting with AI coding agents, enabling users to automate, control, and even enhance its functionalities. With just a single prompt, users can effortlessly modify nearly every aspect of the environment, including the addition of panels, CLI commands, skills, plugins, and workflows, which become instantly accessible to their agents. The platform’s various features, such as GitHub integration, agent memory, scheduled tasks, and remote access, are structured as plugins utilizing the same tools that users can employ. Furthermore, its command line interface supports integration with external applications, such as shell scripts, cron jobs, and messaging bots from Telegram, Signal, and Slack, which can initiate tasks that remain visible in the sidebar. bb accommodates several coding agents, like Claude Code, Codex, Cursor, Pi, OpenCode, Grok, omp, and Hermes, allowing users to delegate tasks to the most appropriate agent or enable one agent to create and oversee another in distinct threads. Additionally, all work is executed on the user's own device, providing the flexibility for tasks to persist and operate autonomously until the user decides to resume their interaction. This level of independence enhances productivity and allows for a seamless workflow experience.

Oqoqo serves as a comprehensive platform for creating evaluations and tailored benchmarks for practical tasks requiring agency, enabling teams to conduct large-scale experiments in realistic settings utilizing fully managed cloud services. Users have the flexibility to establish private sets of tasks and criteria, evaluate agents on their ability to interact with various products such as skills, MCP servers, CLIs, SDKs, APIs, documentation, and files, while also facilitating the comparison of agents, models, interventions, and levels of effort under consistent conditions. Each individual task operates in its own separate environment, complete with the necessary project state, context, files, tools, and credentials. Oqoqo meticulously records every aspect of each run, documenting commands, tool interactions, errors, files, and the point at which an agent ceased functioning, ultimately providing metrics such as pass or fail results, pass rates, improvements, token utilization, and areas of friction. With these valuable insights, teams are empowered to pinpoint issues within product interfaces, address token inefficiencies, analyze performance variances, rectify failures, and subsequently re-execute the experiments for further refinement and learning. This iterative process fosters a culture of continuous improvement, ensuring that agents are consistently enhanced for optimal performance.

Nativ is an entirely open-source application designed for macOS, enabling users to execute OpenAI models locally on Apple Silicon, thereby bringing cutting-edge intelligence directly to your workspace without the need for accounts or cloud infrastructure. It features an intuitive chat interface that facilitates streaming responses, supports Markdown and code highlighting, accepts image inputs, and offers performance metrics for each message, all while ensuring that responses are generated locally on the device. The app includes a curated library of models from various teams, such as Google, Cohere, and Liquid AI, and it intelligently suggests models that align with the specifications of your Mac hardware. Built on the MLX-VLM architecture and optimized for M-series unified memory and Metal, Nativ operates models seamlessly without the need for wrappers or translation layers. Users benefit from live telemetry that provides insights into tokens processed per second, memory usage, thermal conditions, and the time taken to generate the first token, giving a clear view of the inference process. Furthermore, Nativ accommodates diverse workflows, including language processing, vision tasks, video analysis, code assistance, and audio manipulation, allowing users to engage in activities like conversing with LLMs, generating image captions, summarizing video content, auto-completing code snippets, transcribing audio files, and producing speech outputs. This versatility makes Nativ an invaluable tool for developers and creators looking to harness local AI capabilities.

OpenAI’s GPT-5 represents the cutting edge in AI language models, designed to be smarter, faster, and more reliable across diverse applications such as legal analysis, scientific research, and financial modeling. This flagship model incorporates built-in “thinking” to deliver accurate, professional, and nuanced responses that help users solve complex problems. With a massive context window and high token output limits, GPT-5 supports extensive conversations and intricate coding tasks with minimal prompting. It introduces advanced features like the verbosity parameter, enabling users to control the detail and tone of generated content. GPT-5 also integrates seamlessly with enterprise data sources like Google Drive and SharePoint, enhancing response relevance with company-specific knowledge while ensuring data privacy. The model’s improved personality and steerability make it adaptable for a wide range of business needs. Available in ChatGPT and API platforms, GPT-5 brings expert intelligence to every user, from casual individuals to large organizations. Its release marks a major step forward in AI-assisted productivity and collaboration.

Superwhisper is an AI voice-to-text platform that helps users speak naturally and turn their words into polished writing across any app. The product supports dictation, meeting recording, file transcription, push-to-talk, shortcuts, custom modes, vocabulary controls, and AI-enhanced formatting. Superwhisper works anywhere users can type, including productivity apps, messaging tools, coding environments, and agentic AI workflows. Developers can use it with Cursor, Claude Code, OpenCode, Amp, Codex, Grok CLI, and other coding agents to provide richer context without typing long prompts. Custom Mode lets users define how Superwhisper thinks, writes, formats, and responds for different tasks or applications. Users can choose from language models such as GPT, Claude, Llama, Grok, Gemini, Ministral, and others to balance speed, accuracy, and complexity. The platform also supports voice models such as Whisper Large and can transcribe audio and video files. Its adaptability features help users shift between casual messages, professional emails, legal language, multilingual workflows, and specialized writing styles. By combining dictation, transcription, model selection, custom prompts, vocabulary, app integrations, and agentic coding support, Superwhisper helps users move faster with their voice.

Introducing Gemma 3n, our cutting-edge open multimodal model designed specifically for optimal on-device performance and efficiency. With a focus on responsive and low-footprint local inference, Gemma 3n paves the way for a new generation of intelligent applications that can be utilized on the move. It has the capability to analyze and respond to a blend of images and text, with plans to incorporate video and audio functionalities in the near future. Developers can create smart, interactive features that prioritize user privacy and function seamlessly without an internet connection. The model boasts a mobile-first architecture, significantly minimizing memory usage. Co-developed by Google's mobile hardware teams alongside industry experts, it maintains a 4B active memory footprint while also offering the flexibility to create submodels for optimizing quality and latency. Notably, Gemma 3n represents our inaugural open model built on this revolutionary shared architecture, enabling developers to start experimenting with this advanced technology today in its early preview. As technology evolves, we anticipate even more innovative applications to emerge from this robust framework.

The latest iteration in the GPT-5 series, known as GPT-5.1, aims to significantly enhance the intelligence and conversational abilities of ChatGPT. This update features two separate model types: GPT-5.1 Instant, recognized as the most popular option, is characterized by a warmer demeanor, improved instruction adherence, and heightened intelligence; on the other hand, GPT-5.1 Thinking has been fine-tuned as an advanced reasoning engine, making it easier to grasp, quicker for simpler tasks, and more diligent when tackling complex issues. Additionally, queries from users are now intelligently directed to the model variant that is best equipped for the specific task at hand. This update not only focuses on boosting raw cognitive capabilities but also on refining the communication style, resulting in models that are more enjoyable to interact with and better aligned with users' intentions. Notably, the system card addendum indicates that GPT-5.1 Instant employs a feature called "adaptive reasoning," allowing it to determine when deeper thought is necessary before formulating a response, while GPT-5.1 Thinking adjusts its reasoning time precisely in relation to the complexity of the question posed. Ultimately, these advancements mark a significant step forward in making AI interactions more intuitive and user-friendly.

The GPT-5.2 Thinking variant represents the pinnacle of capability within OpenAI's GPT-5.2 model series, designed specifically for in-depth reasoning and the execution of intricate tasks across various professional domains and extended contexts. Enhancements made to the core GPT-5.2 architecture focus on improving grounding, stability, and reasoning quality, allowing this version to dedicate additional computational resources and analytical effort to produce responses that are not only accurate but also well-structured and contextually enriched, especially in the face of complex workflows and multi-step analyses. Excelling in areas that demand continuous logical consistency, GPT-5.2 Thinking is particularly adept at detailed research synthesis, advanced coding and debugging, complex data interpretation, strategic planning, and high-level technical writing, showcasing a significant advantage over its simpler counterparts in assessments that evaluate professional expertise and deep understanding. This advanced model is an essential tool for professionals seeking to tackle sophisticated challenges with precision and expertise.

The GPT-5.2 Instant model represents a swift and efficient iteration within OpenAI's GPT-5.2 lineup, tailored for routine tasks and learning, showcasing notable advancements in responding to information-seeking inquiries, how-to guidance, technical documentation, and translation tasks compared to earlier models. This version builds upon the more engaging conversational style introduced in GPT-5.1 Instant, offering enhanced clarity in its explanations that prioritize essential details, thus facilitating quicker access to precise answers for users. With its enhanced speed and responsiveness, GPT-5.2 Instant is adept at performing common functions such as handling inquiries, creating summaries, supporting research efforts, and aiding in writing and editing tasks, while also integrating extensive enhancements from the broader GPT-5.2 series that improve reasoning abilities, manage longer contexts, and ensure factual accuracy. As a part of the GPT-5.2 family, it benefits from shared foundational improvements that elevate its overall reliability and performance for a diverse array of daily activities. Users can expect a more intuitive interaction experience and a significant reduction in the time spent searching for information.

The Pro version of OpenAI’s latest GPT-5.2 model family, known as GPT-5.2 Pro, stands out as the most advanced offering, designed to provide exceptional reasoning capabilities, tackle intricate tasks, and achieve heightened accuracy suitable for high-level knowledge work, innovative problem-solving, and enterprise applications. Building upon the enhancements of the standard GPT-5.2, it features improved general intelligence, enhanced understanding of longer contexts, more reliable factual grounding, and refined tool usage, leveraging greater computational power and deeper processing to deliver thoughtful, dependable, and contextually rich responses tailored for users with complex, multi-step needs. GPT-5.2 Pro excels in managing demanding workflows, including sophisticated coding and debugging, comprehensive data analysis, synthesis of research, thorough document interpretation, and intricate project planning, all while ensuring greater accuracy and reduced error rates compared to its less robust counterparts. This makes it an invaluable tool for professionals seeking to optimize their productivity and tackle substantial challenges with confidence.

Gemini 3 Flash is a next-generation AI model created to deliver powerful intelligence without sacrificing speed. Built on the Gemini 3 foundation, it offers advanced reasoning and multimodal capabilities with significantly lower latency. The model adapts its thinking depth based on task complexity, optimizing both performance and efficiency. Gemini 3 Flash is engineered for agentic workflows, iterative development, and real-time applications. Developers benefit from faster inference and strong coding performance across benchmarks. Enterprises can deploy it at scale through Vertex AI and Gemini Enterprise. Consumers experience faster, smarter assistance across the Gemini app and Search. Gemini 3 Flash makes high-performance AI practical for everyday use.

Intent is a public beta desktop workspace tailored for specification-driven development and the orchestration of multiple agents, empowering developers to strategize, carry out, and refine intricate coding tasks through the collaboration of synchronized AI agents. Central to its workflow are dynamic specifications, which enable teams to articulate their project requirements while allowing the agents to carry out those tasks and continuously update the specifications to mirror the actual results. The platform offers a cohesive environment where various agents can operate simultaneously without causing conflicts, thereby removing the hassle of managing multiple terminals, branches, or dispersed prompts. Enhanced by Augment’s Context Engine, each agent possesses a comprehensive understanding of the entire codebase, which guarantees coherence across the planning, execution, and verification phases. Intent is compatible with leading-edge models and provides flexibility for developers to select and combine them according to the complexity of their tasks, whether it’s for designing architecture, executing rapid iterations, or conducting in-depth code analysis. By streamlining these processes, Intent aims to enhance productivity and collaboration within development teams.

The Z.ai DevPack, known as the GLM Coding Plan, is a subscription-driven AI coding service aimed at enhancing coding efficiency by seamlessly incorporating high-performance language models into existing software development platforms. This service grants users access to sophisticated models like GLM-4.7 and GLM-5, which are compatible with leading AI coding environments such as Claude Code, Cline, OpenCode, and various other tools that utilize OpenAI-compatible APIs. By enabling developers to articulate their requirements in natural language, the system can automatically produce code, troubleshoot problems, and perform various tasks, while also providing real-time, context-sensitive code completion that significantly boosts productivity. Additionally, the platform features advanced debugging and repair functionalities, empowering models to detect errors, propose solutions, and ensure consistent execution throughout the development cycle. With its user-friendly and organized interface, DevPack facilitates effortless communication between different tools and models, optimizing the overall coding experience. This innovative approach not only streamlines workflows but also enhances collaboration among developers and AI technologies.

Paperclip is a self-hosted agent management platform designed to help users organize and operate AI agents as structured teams rather than standalone assistants. The platform provides organizational hierarchies, role-based agent assignments, ticket management, budget controls, and governance mechanisms that enable multiple agents to collaborate on business goals. Supporting a wide range of AI providers and agent frameworks, Paperclip allows organizations to build customized AI workforces for tasks such as software development, marketing, quality assurance, research, outreach, and operations. Its open-source architecture and extensible design give teams complete ownership of their infrastructure while ensuring visibility into every decision, action, and resource consumed by AI agents.

Superpowers is an agentic software development framework that provides coding agents with a complete methodology for building software more carefully and consistently. The framework is built around composable skills that automatically guide agents through the right workflow at each stage of development. Instead of immediately generating code, an agent using Superpowers first clarifies the user’s goal, develops a specification, and presents the design in readable sections for approval. Once the design is approved, the agent creates a detailed implementation plan with small tasks, exact file paths, verification steps, and testing expectations. Superpowers strongly emphasizes true test-driven development, including writing failing tests first, making them pass, refactoring, and committing only after verification. The framework can use subagents to complete tasks, inspect work, review implementation quality, and continue progressing through a structured plan. It includes skills for brainstorming, writing plans, executing plans, systematic debugging, code review, git worktrees, and finishing development branches. Superpowers supports multiple coding environments, including Claude Code, Codex, Gemini CLI, OpenCode, Cursor, Factory Droid, and GitHub Copilot CLI. Superpowers helps software teams reduce agentic mistakes, improve code quality, and make AI-assisted development more predictable.

Tencent HY is a versatile and comprehensive family of large models developed in-house by Tencent, designed to deliver AI solutions tailored for enterprise needs across various domains such as content creation, business automation, and real-world agent functionalities. It encompasses multiple modalities, including language, imagery, 3D modeling, and translation, seamlessly integrating Tencent’s proprietary algorithms with advanced natural language processing and computer vision technologies to enable superior image generation, 3D content creation, and intelligent applications. Via Tencent Hunyuan AI Studio, users can engage with the model through intuitive human-computer dialogue, which allows the system to comprehend commands, perform tasks, assist users in information retrieval, generate content, and discover the model's extensive capabilities in a user-friendly environment. Additionally, Tencent HY facilitates API integration and customizable parameter configurations, enhancing accessibility and usability for developers, product teams, and enterprise-focused applications. This adaptability ensures that a wide range of users can leverage the power of Tencent HY in their projects, driving innovation and efficiency across industries.

The Meta Model API is an innovative developer interface designed for utilizing Muse Spark 1.1, Meta's advanced multimodal reasoning model tailored for agentic tasks such as coding, tool utilization, and comprehensive computer interactions. Currently available in public preview, this API enables developers to seamlessly integrate Muse Spark 1.1 via an OpenAI-compatible package, simplifying the transition for existing clients while maintaining the same code framework and allowing for easy configuration to the muse-spark-1.1 model. This model excels in personal agentic functions, facilitating planning and coordination across various external applications and services, while also adapting to new native tools, MCP servers, and bespoke skills. Functioning as a primary agent, it can collect contextual information, devise plans, and oversee execution across multiple subagents; conversely, as a subagent, it adheres to its designated role, comprehends available tools, and recognizes when to escalate issues. Additionally, the model is capable of managing a context window of 1 million tokens, allowing it to remember past actions, retrieve information from significantly earlier tasks, and effectively condense context for optimal performance. With these capabilities, the Meta Model API represents a significant advancement in the development of intelligent, responsive applications.

AgentScan is a no-cost, deterministic security scanner specifically designed for evaluating AI agent skills. It meticulously inspects a skill directory, which includes platforms like Claude Code, Codex, OpenCode, and MCP servers, for various vulnerabilities such as prompt injection, hidden secrets, network activity, malware signatures, and obfuscation techniques prior to installation. Each identified issue is accompanied by specific file:line references and an associated confidence score. The tool operates without executing the skill or uploading any data, functioning entirely offline. Being free and open-source under the MIT license, it also offers the Trust Pack feature, which facilitates the addition of 90 pre-audited skills with a single command. This ensures users can enhance their security measures efficiently.