OpenClaw Integrations

Kimi is a highly capable assistant equipped with an extensive "memory" that allows her to read lengthy novels of up to 200,000 words and browse the Internet simultaneously. With her ability to comprehend and analyze long documents, Kimi is invaluable for quickly summarizing reports such as financial analyses and research findings, thereby streamlining your reading and organizational tasks. When it comes to studying for exams or delving into new subjects, Kimi can efficiently summarize and clarify complex information from textbooks or academic papers. For those engaged in programming or tech-related tasks, Kimi offers support by reproducing code or suggesting technical solutions based on your input, whether it's code snippets or pseudocode from your documents. Proficient in Chinese and capable of managing multilingual content, Kimi enhances communication and understanding in international settings, making her a versatile tool for global collaboration. Additionally, Kimi Chat can engage you in dynamic conversations or even embody your favorite game characters, providing both entertainment and a way to unwind. Not only does Kimi assist with productivity, but she also brings a fun and interactive element to your daily routine.

FLUX.1 represents a revolutionary suite of open-source text-to-image models created by Black Forest Labs, achieving new heights in AI-generated imagery with an impressive 12 billion parameters. This model outperforms established competitors such as Midjourney V6, DALL-E 3, and Stable Diffusion 3 Ultra, providing enhanced image quality, intricate details, high prompt fidelity, and adaptability across a variety of styles and scenes. The FLUX.1 suite is available in three distinct variants: Pro for high-end commercial applications, Dev tailored for non-commercial research with efficiency on par with Pro, and Schnell designed for quick personal and local development initiatives under an Apache 2.0 license. Notably, its pioneering use of flow matching alongside rotary positional embeddings facilitates both effective and high-quality image synthesis. As a result, FLUX.1 represents a significant leap forward in the realm of AI-driven visual creativity, showcasing the potential of advancements in machine learning technology. This model not only elevates the standard for image generation but also empowers creators to explore new artistic possibilities.

Qwen3 is a state-of-the-art large language model designed to revolutionize the way we interact with AI. Featuring both thinking and non-thinking modes, Qwen3 allows users to customize its response style, ensuring optimal performance for both complex reasoning tasks and quick inquiries. With the ability to support 119 languages, the model is suitable for international projects. The model's hybrid training approach, which involves over 36 trillion tokens, ensures accuracy across a variety of disciplines, from coding to STEM problems. Its integration with platforms such as Hugging Face, ModelScope, and Kaggle allows for easy adoption in both research and production environments. By enhancing multilingual support and incorporating advanced AI techniques, Qwen3 is designed to push the boundaries of AI-driven applications.

ByteRover serves as an innovative memory enhancement layer tailored for AI coding agents, facilitating the creation, retrieval, and sharing of "vibe-coding" memories among various projects and teams. Crafted for a fluid AI-supported development environment, it seamlessly integrates into any AI IDE through the Memory Compatibility Protocol (MCP) extension, allowing agents to automatically save and retrieve contextual information without disrupting existing workflows. With features such as instantaneous IDE integration, automated memory saving and retrieval, user-friendly memory management tools (including options to create, edit, delete, and prioritize memories), and collaborative intelligence sharing to uphold uniform coding standards, ByteRover empowers developer teams, regardless of size, to boost their AI coding productivity. This approach not only reduces the need for repetitive training but also ensures the maintenance of a centralized and easily searchable memory repository. By installing the ByteRover extension in your IDE, you can quickly begin harnessing and utilizing agent memory across multiple projects in just a few seconds, leading to enhanced team collaboration and coding efficiency.

Qwen3-Coder is a versatile coding model that comes in various sizes, prominently featuring the 480B-parameter Mixture-of-Experts version with 35B active parameters, which naturally accommodates 256K-token contexts that can be extended to 1M tokens. This model achieves impressive performance that rivals Claude Sonnet 4, having undergone pre-training on 7.5 trillion tokens, with 70% of that being code, and utilizing synthetic data refined through Qwen2.5-Coder to enhance both coding skills and overall capabilities. Furthermore, the model benefits from post-training techniques that leverage extensive, execution-guided reinforcement learning, which facilitates the generation of diverse test cases across 20,000 parallel environments, thereby excelling in multi-turn software engineering tasks such as SWE-Bench Verified without needing test-time scaling. In addition to the model itself, the open-source Qwen Code CLI, derived from Gemini Code, empowers users to deploy Qwen3-Coder in dynamic workflows with tailored prompts and function calling protocols, while also offering smooth integration with Node.js, OpenAI SDKs, and environment variables. This comprehensive ecosystem supports developers in optimizing their coding projects effectively and efficiently.

FLUX.1 Krea [dev] is a cutting-edge, open-source diffusion transformer with 12 billion parameters, developed through the collaboration of Krea and Black Forest Labs, aimed at providing exceptional aesthetic precision and photorealistic outputs while avoiding the common “AI look.” This model is fully integrated into the FLUX.1-dev ecosystem and is built upon a foundational model (flux-dev-raw) that possesses extensive world knowledge. It utilizes a two-phase post-training approach that includes supervised fine-tuning on a carefully selected combination of high-quality and synthetic samples, followed by reinforcement learning driven by human feedback based on preference data to shape its stylistic outputs. Through the innovative use of negative prompts during pre-training, along with custom loss functions designed for classifier-free guidance and specific preference labels, it demonstrates substantial enhancements in quality with fewer than one million examples, achieving these results without the need for elaborate prompts or additional LoRA modules. This approach not only elevates the model's output but also sets a new standard in the field of AI-driven visual generation.

Qwen3-Max represents Alibaba's cutting-edge large language model, featuring a staggering trillion parameters aimed at enhancing capabilities in tasks that require agency, coding, reasoning, and managing lengthy contexts. This model is an evolution of the Qwen3 series, leveraging advancements in architecture, training methods, and inference techniques; it integrates both thinker and non-thinker modes, incorporates a unique “thinking budget” system, and allows for dynamic mode adjustments based on task complexity. Capable of handling exceptionally lengthy inputs, processing hundreds of thousands of tokens, it also supports tool invocation and demonstrates impressive results across various benchmarks, including coding, multi-step reasoning, and agent evaluations like Tau2-Bench. While the initial version prioritizes instruction adherence in a non-thinking mode, Alibaba is set to introduce reasoning functionalities that will facilitate autonomous agent operations in the future. In addition to its existing multilingual capabilities and extensive training on trillions of tokens, Qwen3-Max is accessible through API interfaces that align seamlessly with OpenAI-style functionalities, ensuring broad usability across applications. This comprehensive framework positions Qwen3-Max as a formidable player in the realm of advanced artificial intelligence language models.

GLM-4.6 builds upon the foundations laid by its predecessor, showcasing enhanced reasoning, coding, and agent capabilities, resulting in notable advancements in inferential accuracy, improved tool usage during reasoning tasks, and a more seamless integration within agent frameworks. In comprehensive benchmark evaluations that assess reasoning, coding, and agent performance, GLM-4.6 surpasses GLM-4.5 and competes robustly against other models like DeepSeek-V3.2-Exp and Claude Sonnet 4, although it still lags behind Claude Sonnet 4.5 in terms of coding capabilities. Furthermore, when subjected to practical tests utilizing an extensive “CC-Bench” suite that includes tasks in front-end development, tool creation, data analysis, and algorithmic challenges, GLM-4.6 outperforms GLM-4.5 while nearing parity with Claude Sonnet 4, achieving victory in approximately 48.6% of direct comparisons and demonstrating around 15% improved token efficiency. This latest model is accessible through the Z.ai API, providing developers the flexibility to implement it as either an LLM backend or as the core of an agent within the platform's API ecosystem. In addition, its advancements could significantly enhance productivity in various application domains, making it an attractive option for developers looking to leverage cutting-edge AI technology.

Qwen3-VL represents the latest addition to Alibaba Cloud's Qwen model lineup, integrating sophisticated text processing with exceptional visual and video analysis capabilities into a cohesive multimodal framework. This model accommodates diverse input types, including text, images, and videos, and it is adept at managing lengthy and intertwined contexts, supporting up to 256 K tokens with potential for further expansion. With significant enhancements in spatial reasoning, visual understanding, and multimodal reasoning, Qwen3-VL's architecture features several groundbreaking innovations like Interleaved-MRoPE for reliable spatio-temporal positional encoding, DeepStack to utilize multi-level features from its Vision Transformer backbone for improved image-text correlation, and text–timestamp alignment for accurate reasoning of video content and time-related events. These advancements empower Qwen3-VL to analyze intricate scenes, track fluid video narratives, and interpret visual compositions with a high degree of sophistication. The model's capabilities mark a notable leap forward in the field of multimodal AI applications, showcasing its potential for a wide array of practical uses.

GLM-4.7 is a next-generation AI model built to serve as a powerful coding and reasoning partner. It improves significantly on its predecessor across software engineering, multilingual coding, and terminal interaction benchmarks. GLM-4.7 introduces enhanced agentic behavior by thinking before tool use or execution, improving reliability in long and complex tasks. The model demonstrates strong performance in real-world coding environments and popular coding agents. GLM-4.7 also advances visual and frontend generation, producing modern UI designs and well-structured presentation slides. Its improved tool-use capabilities allow it to browse, analyze, and interact with external systems more effectively. Mathematical and logical reasoning have been strengthened through higher benchmark performance on challenging exams. The model supports flexible reasoning modes, allowing users to trade latency for accuracy. GLM-4.7 can be accessed via Z.ai, OpenRouter, and agent-based coding tools. It is designed for developers who need high performance without excessive cost.

MiniMax-M2.1 is a state-of-the-art open-source AI model built specifically for agent-based development and real-world automation. It focuses on delivering strong performance in coding, tool calling, and long-term task execution. Unlike closed models, MiniMax-M2.1 is fully transparent and can be deployed locally or integrated through APIs. The model excels in multilingual software engineering tasks and complex workflow automation. It demonstrates strong generalization across different agent frameworks and development environments. MiniMax-M2.1 supports advanced use cases such as autonomous coding, application building, and office task automation. Benchmarks show significant improvements over previous MiniMax versions. The model balances high reasoning ability with stability and control. Developers can fine-tune or extend it for specialized agent workflows. MiniMax-M2.1 empowers teams to build reliable AI agents without vendor lock-in.

Zernio is a unified social media API platform that enables developers and AI agents to publish, schedule, and manage content across 14+ social networks through a single integration. Instead of building and maintaining separate integrations with each platform's API, developers make one API call and Zernio handles authentication, media formatting, rate limits, and platform-specific requirements. The platform supports Instagram Business and Creator APIs, TikTok Business API, LinkedIn Company and Personal APIs, YouTube Data API, Twitter/X API, Facebook Graph API, Meta Business Suite, Pinterest API, Google My Business API, Reddit API, Threads API, Bluesky API, and WhatsApp Business API. Key capabilities include post scheduling and publishing, content management across all platforms, comments and DMs automation, analytics tracking, ads management, media upload and management, webhook notifications, rate limit management, and automatic token refresh. Zernio is designed for developers and technical teams building products that require social media functionality, including SaaS companies embedding social features into their own products, agencies managing client accounts at scale, and AI agent builders who need programmatic social posting. The product is white-label, meaning end users never see Zernio branding. Developer-friendly SDKs and comprehensive API documentation support fast implementation, reducing integration time from months to under an hour. A free version and free trial are available, with usage-based pricing.

Qwen3-TTS represents an innovative collection of advanced text-to-speech models created by the Qwen team at Alibaba Cloud, released under the Apache-2.0 license, which delivers stable, expressive, and real-time speech output with functionalities like voice cloning, voice design, and precise control over prosody and acoustic features. This suite supports ten prominent languages—Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, and Italian—along with various dialect-specific voice profiles, enabling adaptive management of tone, speech rate, and emotional delivery tailored to text semantics and user instructions. The architecture of Qwen3-TTS incorporates efficient tokenization and a dual-track design, facilitating ultra-low-latency streaming synthesis, with the first audio packet generated in approximately 97 milliseconds, making it ideal for interactive and real-time applications. Additionally, the range of models available offers diverse capabilities, such as rapid three-second voice cloning, customization of voice timbres, and voice design based on given instructions, ensuring versatility for users in many different scenarios. This flexibility in design and performance highlights the model's potential for a wide array of applications in both commercial and personal contexts.

Kimi Code CLI serves as an AI-driven command-line tool designed to aid developers in software creation and terminal tasks by interpreting and altering code, executing shell commands, retrieving web content, autonomously strategizing and modifying actions during processes, and offering an interactive shell environment where users can articulate their requirements in everyday language or switch to command mode for direct input; it seamlessly integrates with IDEs and local agent clients through the Agent Client Protocol, enhancing workflows and streamlining activities like code writing, bug fixing, project exploration, addressing architectural queries, and automating batch processes or build and test scripts. The installation process involves running a script that sets up the essential tool manager before downloading the Kimi CLI package, after which users can confirm installation with a version check and proceed to configure an API source for optimal functionality. Additionally, the Kimi Code CLI not only enhances productivity but also fosters a more intuitive interaction between developers and their coding environment.

happycapy serves as an agent-native AI platform that transforms your web browser into a robust "agent computer," allowing developers and users to launch and operate autonomous AI agents around the clock without relying on conventional server setups. This innovation enables the delegation of tasks to numerous large language models (LLMs) and AI services, including Claude Code, all within a secure, sandboxed environment. By facilitating the simultaneous operation of multiple AI agents, happycapy effectively manages coding, automation, data processing, and custom workflows, providing teams with a cohesive interface for orchestrating, scaling, and monitoring agent-related activities. The platform prioritizes flexibility and developer autonomy through a private sandbox, where agents can perform tasks, engage with code and data, and collaborate on intricate projects while overseeing state, logs, and outputs from various AI services. Additionally, happycapy streamlines the development and upkeep of AI-driven applications by simplifying the complexities associated with infrastructure and model management. This makes it easier for teams to harness the full potential of AI technology in their workflows.

Qwen3-Coder-Next is a language model with open weights, crafted for coding agents and local development, which excels in advanced coding reasoning, adept tool usage, and effective handling of long-term programming challenges with remarkable efficiency, utilizing a mixture-of-experts framework that harmonizes robust capabilities with a resource-efficient approach. This model enhances the coding prowess of software developers, AI system architects, and automated coding processes, allowing them to generate, debug, and comprehend code with a profound contextual grasp while adeptly recovering from execution errors, rendering it ideal for autonomous coding agents and applications focused on development. Furthermore, Qwen3-Coder-Next achieves impressive performance on par with larger parameter models, but does so while consuming fewer active parameters, thus facilitating economical deployment for intricate and evolving programming tasks in both research and production settings, ultimately contributing to a more streamlined development process.

MiniMax M2.5 is a next-generation foundation model built to power complex, economically valuable tasks with speed and cost efficiency. Trained using large-scale reinforcement learning across hundreds of thousands of real-world task environments, it excels in coding, tool use, search, and professional office workflows. In programming benchmarks such as SWE-Bench Verified and Multi-SWE-Bench, M2.5 reaches state-of-the-art levels while demonstrating improved multilingual coding performance. The model exhibits architect-level reasoning, planning system structure and feature decomposition before writing code. With throughput speeds of up to 100 tokens per second, it completes complex evaluations significantly faster than earlier versions. Reinforcement learning optimizations enable more precise search rounds and fewer reasoning steps, improving overall efficiency. M2.5 is available in two variants—standard and Lightning—offering identical capabilities with different speed configurations. Pricing is designed to be dramatically lower than competing frontier models, reducing cost barriers for large-scale agent deployment. Integrated into MiniMax Agent, the model supports advanced office skills including Word formatting, Excel financial modeling, and PowerPoint editing. By combining high performance, efficiency, and affordability, MiniMax M2.5 aims to make agent-powered productivity accessible at scale.

Atomic Bot serves as a straightforward AI assistant app that harnesses the power of the OpenClaw autonomous agent framework within an easy-to-navigate interface, enabling users to automate various digital tasks without the need for complicated configurations. This application can operate either locally on your device or in the cloud utilizing your own LLM API keys, thereby granting users full control and safeguarding their data privacy. Additionally, it accommodates several AI models, including Claude, GPT, and Gemini, allowing you to select the engine that best aligns with your workflow requirements. Atomic Bot features persistent memory to retain preferences and tasks, adapts to your working habits over time, and can perform web-based tasks by navigating websites, executing processes, completing forms, and gathering information directly from chats. Furthermore, it is capable of automating recurring and scheduled tasks, keeping an eye on important matters, organizing files, and connecting with various everyday tools to enhance professional productivity. With its intuitive design and robust functionality, Atomic Bot not only simplifies task management but also elevates your overall efficiency in both personal and professional settings.

DeepSeek-V4 is an advanced open-source large language model engineered for efficient long-context processing and high-level reasoning tasks. Supporting a massive one million token context window, it enables developers to build applications that handle extensive data and complex workflows without fragmentation. The model is available in two versions: V4-Pro for maximum reasoning power and V4-Flash for faster, cost-efficient performance. DeepSeek-V4-Pro delivers top-tier results in coding, mathematics, and knowledge benchmarks, rivaling leading proprietary models. Its architecture incorporates innovative attention techniques that significantly improve efficiency while maintaining strong performance. The model is optimized for agent-based workflows, allowing seamless integration with tools and automation systems. It also supports dual reasoning modes, enabling users to switch between quick responses and deeper analytical outputs. DeepSeek-V4 is fully open-source, providing flexibility for customization and deployment across various environments. Overall, it offers a powerful and scalable solution for modern AI development.

AGBCLOUD is a cloud-based sandbox platform designed for AI that offers developers and organizations secure and isolated environments to create and manage autonomous software agents. This platform provides agents with fully-equipped cloud development environments that facilitate multilingual code generation, compilation, and debugging through easily accessible browser sandboxes. By allowing advanced functionalities such as web browsing, computer interactions, and data analysis, AGBCLOUD ensures that AI systems can engage with files, applications, and the internet safely within a controlled space. Furthermore, it incorporates plug-and-play MCP tools alongside LLM-driven analytics to convert raw data into meaningful insights and dynamic applications. The sandbox architecture supports cross-platform capabilities, enabling agents to transition effortlessly between coding, browsing, and system-level tasks, all while upholding stringent security and isolation measures. This versatility opens up new possibilities for developers seeking to enhance their AI solutions.

Qwen3.5 represents a major advancement in open-weight multimodal AI models, engineered to function as a native vision-language agent system. Its flagship model, Qwen3.5-397B-A17B, leverages a hybrid architecture that fuses Gated DeltaNet linear attention with a high-sparsity mixture-of-experts framework, allowing only 17 billion parameters to activate during inference for improved speed and cost efficiency. Despite its sparse activation, the full 397-billion-parameter model achieves competitive performance across reasoning, coding, multilingual benchmarks, and complex agent evaluations. The hosted Qwen3.5-Plus version supports a one-million-token context window and includes built-in tool use for search, code interpretation, and adaptive reasoning. The model significantly expands multilingual coverage to 201 languages and dialects while improving encoding efficiency with a larger vocabulary. Native multimodal training enables strong performance in image understanding, video processing, document analysis, and spatial reasoning tasks. Its infrastructure includes FP8 precision pipelines and heterogeneous parallelism to boost throughput and reduce memory consumption. Reinforcement learning at scale enhances multi-step planning and general agent behavior across text and multimodal environments. Overall, Qwen3.5 positions itself as a high-efficiency foundation for autonomous digital agents capable of reasoning, searching, coding, and interacting with complex environments.

IronClaw is an open-source runtime that prioritizes security, designed specifically for the execution of autonomous AI agents while incorporating robust protections for sensitive credentials and system access. This platform serves as a security-centric alternative to OpenClaw, functioning within encrypted enclaves on the NEAR AI Cloud or locally to safeguard sensitive information during its operation. Users can effortlessly launch AI agents via a one-click setup, ensuring that API keys, tokens, and passwords are securely stored in an encrypted vault, inaccessible to the AI itself. IronClaw takes security further by isolating each tool within its own WebAssembly sandbox, employing capability-based permissions and enforcing strict resource limitations to ensure that any compromised functionalities do not jeopardize the overall system. Constructed in Rust, it upholds memory safety at compile time, successfully mitigating common vulnerabilities like buffer overflows and use-after-free errors. With these features, IronClaw not only enhances the security of AI deployments but also instills confidence in users regarding the integrity of their sensitive data throughout the execution process.

ClawGTM is an innovative go-to-market platform powered by AI that streamlines outbound sales processes by converting a business's website into a smart lead-generation and outreach tool. It begins by evaluating a company’s product site or landing page to discern its value proposition, intended audience, and ideal customer profile. Following this analysis, the platform systematically scours extensive datasets, including job advertisements and various market indicators, to pinpoint businesses likely in need of the product. By examining hiring trends, shifts within organizations, and other markers of commercial activity, it identifies genuine buying signals that imply a potential client is experiencing issues that the product can address. Once promising companies and key decision-makers are recognized, the system conducts in-depth research on each lead, crafting personalized outreach messages that are specifically suited to the unique circumstances of each company. This tailored approach enhances the likelihood of engagement and increases the effectiveness of the sales efforts.

The Claude Marketplace serves as a vital component within the Claude AI ecosystem, providing a space for developers and organizations to find, install, and share various extensions that enhance the functionalities of Claude-powered applications and agents. Acting as a unified repository, the marketplace hosts an array of plugins, tools, and "skills" that significantly broaden the capabilities of Claude beyond its foundational AI features. Users can access specialized functionalities through these extensions, including capabilities like external data retrieval, automated web browsing, integrations with third-party APIs, and tailored workflows in fields such as DevOps, research, analytics, and software development. Through the installation of these extensions, Claude can evolve from a standard conversational AI into a versatile platform adept at performing intricate tasks and engaging with various systems. Furthermore, the marketplace empowers developers to create and share plugins that seamlessly integrate with Claude’s operational environment, fostering a collaborative ecosystem that encourages innovation and customization. This collaborative spirit not only enhances user experience but also promotes ongoing advancements in AI technology.

The Kling 3.0 Omni model represents an innovative generative video platform that crafts creative videos from text inputs, images, or other reference materials by utilizing cutting-edge multimodal AI technology. This system enables the production of seamless video clips with duration options that span from about 3 to 15 seconds, perfect for creating brief cinematic sequences that align closely with user prompts. Additionally, it accommodates both prompt-driven video creation and workflows based on visual references, allowing users to input images or other visual cues to influence the scene's subject, style, or composition. By enhancing prompt fidelity and maintaining subject consistency, the model ensures that characters, objects, and environments exhibit stability throughout the duration of the video while also delivering realistic motion and visual coherence. Moreover, the Omni model significantly boosts reference-based generation, ensuring that characters or elements introduced via images retain their recognizability across multiple frames, thereby enriching the overall viewing experience. This capability makes it an invaluable tool for creators seeking to produce visually engaging content with ease and precision.

AgentMail is an innovative email platform that prioritizes API integration, allowing artificial intelligence agents to operate their own complete email inboxes and engage in email exchanges independently. Rather than relying on conventional email services designed for human users, it offers programmatic inboxes that developers can create and manage through an API, permitting the assignment of email identities to AI agents akin to how individuals use Gmail or Outlook accounts. Each AI agent is provided with a dedicated inbox and email address, capable of sending, receiving, and replying to messages while preserving threaded conversations and a continuous message history. This platform empowers AI agents to read and analyze incoming emails, extract relevant information from the messages, and automatically compose replies or initiate workflows based on the discussion's content. Ultimately, AgentMail facilitates seamless communication between AI and users, revolutionizing how machines interact through email.

Mistral Small 4 is a next-generation open-source AI model created by Mistral AI to deliver powerful reasoning, coding, and multimodal capabilities within a single unified architecture. The model merges features from several specialized systems, including Magistral for advanced reasoning, Pixtral for multimodal processing, and Devstral for agentic software development tasks. It supports both text and image inputs, enabling applications such as conversational AI, document analysis, and visual data interpretation. The model is built using a mixture-of-experts design with 128 experts, allowing efficient scaling while maintaining strong performance across diverse tasks. Users can adjust the model’s reasoning behavior through a configurable parameter that toggles between lightweight responses and deeper analytical processing. Mistral Small 4 also provides a large context window that enables it to handle long conversations, detailed documents, and complex reasoning chains. Compared with earlier versions, the model offers improved performance, reduced latency, and higher throughput for real-time applications. Developers can integrate it with popular machine learning frameworks such as Transformers, vLLM, and llama.cpp. The model’s open-source Apache 2.0 license allows organizations to fine-tune and customize it for specialized use cases. By combining efficiency, flexibility, and multimodal intelligence, Mistral Small 4 provides a versatile foundation for building advanced AI-powered applications.

GLM-5-Turbo represents a rapid iteration of Z.ai’s GLM-5 model, engineered to offer both efficient and stable performance specifically tailored for agent-driven scenarios, all while preserving robust reasoning and programming abilities. This model is fine-tuned to handle high-throughput demands, especially in complex long-chain agent tasks that necessitate a series of sequential steps, tools, and decisions executed reliably and with minimal latency. With its support for sophisticated agentic workflows, GLM-5-Turbo enhances multi-step planning, tool utilization, and task execution, delivering superior responsiveness compared to larger flagship models in the lineup. Drawing from the foundational strengths of the GLM-5 family, it maintains strong capabilities in reasoning, coding, and processing extensive contexts, but prioritizes the optimization of essential aspects like speed, efficiency, and stability within production settings. Furthermore, it is crafted to seamlessly integrate with agent frameworks such as OpenClaw, allowing it to proficiently coordinate actions, manage inputs, and carry out tasks effectively. This ensures that users benefit from a responsive and reliable tool that can adapt to various operational demands and complexities.

Rapid Claw is a cloud-based hosting solution designed specifically for OpenClaw, allowing users to quickly set up and operate a fully autonomous AI agent within minutes, all without the need to deal with infrastructure, configuration, or DevOps responsibilities. This platform offers a dedicated and private instance of OpenClaw that runs perpetually in the cloud, enabling the AI agent to carry out essential tasks like managing emails, automating workflows, reviewing code, processing data, and engaging with various applications without any human involvement. By automating the setup, updates, security measures, and backups, it alleviates the challenges commonly associated with self-hosting, which usually entails server provisioning, dependency management, environment setup, and ongoing maintenance. Users can initiate their AI assistant without writing a single line of code, entering API keys, or executing terminal commands, and can start interacting with it immediately through an intuitive interface. This seamless experience makes it accessible for individuals and teams who want to leverage AI capabilities without the technical burden.

Clawdi is an intelligent assistant that functions as a virtual chief of staff, seamlessly integrated into messaging platforms like WhatsApp, Telegram, Slack, and email, allowing users to efficiently handle tasks, workflows, and communication through straightforward chat exchanges. This tool empowers users to activate private AI agents capable of interfacing with numerous business applications to execute real tasks, such as prioritizing emails, organizing calendars, composing reports, and facilitating operations across over 500 connected applications. By prioritizing smooth integration within existing communication platforms, Clawdi minimizes the necessity for users to switch between different tools, thereby centralizing productivity within a chat-based interface. Furthermore, it offers the convenience of one-click deployment for secure, private instances that operate on dedicated infrastructure, ensuring users retain control over their data while enjoying consistent, always-available functionality. With Clawdi, teams can enhance their collaborative efforts and streamline their operations more effectively than ever before.

DockClaw serves as a managed hosting solution for OpenClaw, facilitating the rapid deployment and operation of autonomous AI agents in mere seconds, all without the complexities of server management, Docker, or DevOps configurations. This platform empowers users to effortlessly launch AI-driven agents capable of integrating with various messaging services like Telegram and other communication avenues, enabling them to function continuously for automating workflows, interacting with users, and performing various tasks. With one-click deployment options available on dedicated virtual machines or isolated containers, DockClaw guarantees 24/7 uptime, persistent storage, and health monitoring, ensuring that agents stay consistently operational and reliable. Users benefit from the flexibility of selecting from a range of AI models, such as Claude, GPT, Gemini, Llama, and other systems compatible with OpenAI, with the ability to switch models easily without any vendor lock-in. Furthermore, DockClaw incorporates native configuration tools that allow for the fine-tuning of agent behavior, memory management, and system prompts, while also ensuring secure API key management through encrypted environments and a zero-knowledge architecture. This comprehensive approach not only enhances user experience but also fosters a versatile environment for AI development and deployment.

HostMeNow is a hosting platform that prioritizes privacy by offering offshore solutions designed for secure, anonymous, and efficient performance for websites, applications, and various online services. The platform provides an extensive array of hosting options, including shared hosting with cPanel, virtual private servers (VPS), dedicated servers, reseller hosting, Tor hosting, email services, VPN options, and proxy solutions—all maintained in offshore data centers located in jurisdictions that favor privacy. Significantly, it champions complete anonymity, allowing users to register without the need for identity verification and facilitating payments through cryptocurrencies, thereby granting users total control over their data and personal identity. Hosting environments are tailored for optimal performance, utilizing LiteSpeed web servers, SSD storage, CloudLinux isolation, and advanced caching technologies to guarantee quick load times and dependable service. Additionally, the platform incorporates a multitude of security features, including complimentary SSL certificates, DDoS protection, malware defenses, and regular automated backups, ensuring that both the data and the infrastructure are well-protected. This commitment to privacy and security makes HostMeNow an appealing choice for individuals and businesses alike seeking to establish a robust online presence while maintaining their anonymity.

OneVPS is a cloud-based virtual private server platform that delivers rapid, scalable, and completely customizable hosting solutions tailored for websites and applications. The platform provides VPS offerings with dedicated resources, including Intel processors, SSD storage, adjustable RAM, and adaptable bandwidth, enabling users to modify their server according to specific performance requirements. It prioritizes ease of use and speed, allowing customers to set up a server in just 60 seconds through a straightforward guided procedure, all while granting full root access and comprehensive control over the environment. OneVPS supports a diverse array of development frameworks and applications, such as Java, PHP, Python, and Ruby on Rails, and ensures compatibility with management tools like cPanel to simplify administration. Designed for optimal performance, OneVPS boasts a finely tuned infrastructure featuring ultra-low latency, multiple global data center locations, and high-speed connectivity to guarantee reliable uptime and rapid load times across the globe. Additionally, users can benefit from round-the-clock customer support to assist with any technical issues they may encounter, further enhancing the overall user experience.

InstaClaw is a platform for consumer AI agents that enables individuals to set up a fully autonomous personal AI assistant in just minutes, requiring no coding or technical knowledge, and it offers a dedicated infrastructure for the agent to operate continuously, performing a variety of real-world tasks on the user's behalf. Each AI agent is hosted on its own virtual machine, ensuring constant availability, and can undertake actions like sending emails, managing schedules, browsing the internet, organizing files, conducting research, and automating tasks through simple natural language commands. The platform seamlessly integrates with popular messaging apps such as Telegram, WhatsApp, and iMessage, allowing users to communicate with their agents as if they were sending texts, while the system efficiently manages the execution of tasks in the background. InstaClaw comes equipped with essential pre-installed skills, including web browsing, file organization, and research functionalities, and it offers options for further expansion through additional features and integrations, empowering agents to tackle more complex assignments. This innovative approach not only enhances user productivity but also simplifies the interaction between technology and everyday tasks.

MiniMax M2.7 is a powerful AI model built to drive real-world productivity across coding, search, and office-based workflows. It is trained using reinforcement learning across a wide range of real-world environments, enabling it to execute complex, multi-step tasks with precision and efficiency. The model demonstrates strong problem-solving capabilities by breaking down challenges into structured steps before generating solutions across multiple programming languages. It delivers high-speed performance with rapid token output, ensuring faster completion of demanding tasks. With optimized reasoning, it reduces token usage and execution time, making it more efficient than previous models. M2.7 also achieves state-of-the-art results in software engineering benchmarks, significantly improving response times for technical issues. Its advanced agentic capabilities allow it to work seamlessly with tools and support complex workflows with high skill accuracy. The model is designed to handle professional tasks, including multi-turn interactions and high-quality document editing. It also provides strong support for office productivity, enabling efficient handling of structured data and business tasks. With competitive pricing, it delivers high performance while remaining cost-effective. Overall, it combines speed, intelligence, and versatility to meet the needs of modern professionals and teams.

Blink Claw is an AI-powered platform designed to help users deploy and manage multiple autonomous agents that handle business and personal tasks around the clock. It enables users to create specialized agents for tasks such as managing emails, following up on leads, generating reports, and monitoring workflows with minimal effort. The platform integrates seamlessly with popular tools like Slack, Gmail, Google Calendar, and more, allowing agents to operate within familiar environments. Each agent runs continuously, executing tasks independently and responding to triggers without requiring constant supervision. Blink Claw supports unlimited agents, enabling users to scale their automation as needed. It also includes access to over 200 AI models without requiring separate accounts or API key management. With persistent memory, agents improve over time by learning preferences and workflows. The platform is accessible through messaging apps like Telegram, Discord, and Slack, making interaction simple and intuitive. Its secure infrastructure ensures that data and operations remain private and protected. Overall, Blink Claw provides a scalable and efficient solution for automating workflows and improving productivity.

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.

Superscale is an innovative marketing platform powered by artificial intelligence that streamlines the creation, testing, and scaling of effective advertising campaigns through a unified interface, revolutionizing how teams implement their go-to-market plans. Users can effortlessly generate comprehensive marketing campaigns by entering a product URL, prompting the system to evaluate the product, market dynamics, and positioning in order to craft custom messaging, creative assets, and audience targeting strategies. By integrating various features such as AI-generated video advertisements, copywriting, and creative asset generation, it empowers users to launch fully operational campaigns in mere minutes rather than the traditional weeks. Additionally, the platform includes an integrated studio where users can fine-tune scripts, modify scenes, personalize visuals, and adjust elements like captions, pacing, and audio, all while the AI manages the more demanding aspects of production. This combination of automation and user control ultimately leads to more efficient marketing efforts.

Abacus Claw is a cloud-based platform for AI agents that allows users to create and operate persistent agents that can automate intricate workflows by seamlessly interfacing with common applications and data sources. This system works with platforms like Gmail, Slack, and Google Drive, enabling agents to monitor user behavior, access necessary information, and produce tailored outputs such as summaries, reports, and detailed task lists. In contrast to conventional assistants that function on a single prompt basis, Claw is built for ongoing functionality, allowing agents to be scheduled, activated by specific events, or operate independently to perform complex, multi-step tasks across various systems. Additionally, it offers a managed version of OpenClaw, an open-source framework designed for developing long-lasting AI agents, which empowers users to implement robust automation solutions without needing to manage the underlying infrastructure themselves. This innovative approach not only enhances efficiency but also streamlines the automation process for various business needs.

LarryLoop is a marketing automation platform driven by AI that focuses on the principle of self-sustaining growth loops, where a digital agent oversees the entire content creation and revenue process with minimal human intervention. This system is designed to streamline the entire social media marketing cycle, which encompasses trend research, content generation, post distribution, and performance analysis to enhance results over time. Operating as a cyclic process, the AI produces various content types, including short videos and slideshows, shares them on platforms like TikTok, and assesses metrics such as views, engagement rates, and conversions to fine-tune future content. By seamlessly incorporating analytics and audience feedback into its workflow, LarryLoop facilitates ongoing enhancement of messaging, hooks, and calls to action, enabling content strategies to adapt and grow based on actual performance data rather than mere speculation. Additionally, this dynamic approach helps marketers stay ahead of trends and audience preferences, ensuring that their campaigns remain relevant and effective.

Fastio is an AI-ready content management and collaboration platform that brings teams, clients, and intelligent agents together in a single workspace. The platform allows organizations to manage files, projects, and communications while maintaining full control over permissions and access levels. Users can collaborate in real time through comments, shared workspaces, branded portals, and secure guest access features. Fastio supports seamless integration with leading AI assistants, including ChatGPT, Claude, Gemini, Cursor, and other MCP-enabled systems. Its native AI assistant, Ripley, is included with every workspace and helps users automate tasks, answer questions, and streamline operations. The platform's metadata extraction technology converts unstructured content into structured, searchable information that can be analyzed and queried efficiently. Developers can access the same functionality through REST APIs, command-line tools, SDKs, and MCP integrations. Security features include AES-256 encryption, TLS 1.3 protection, workspace isolation, audit trails, and customizable sharing restrictions. By combining content management, collaboration, automation, and AI connectivity, Fastio helps organizations improve productivity across teams and projects.

Trinity Large Thinking is an innovative open-source reasoning model crafted by Arcee AI, tailored for intricate, multi-step problem solving and workflows involving autonomous agents that necessitate extended planning and the use of various tools. This model features a sparse Mixture-of-Experts architecture, boasting a remarkable total of around 400 billion parameters, with approximately 13 billion being active for each token, which enhances its efficiency while ensuring robust reasoning capabilities across a range of tasks, including mathematical calculations, code generation, and comprehensive analysis. A notable advancement in this model is its ability to perform extended chain-of-thought reasoning, which allows it to produce intermediate "thinking traces" prior to delivering final solutions, thereby boosting accuracy and reliability in complex situations. Furthermore, Trinity Large Thinking accommodates a substantial context window of up to 262K tokens, allowing it to effectively process lengthy documents, retain context during prolonged interactions, and function seamlessly in continuous agent loops. This model's design reflects a commitment to pushing the boundaries of what automated reasoning systems can achieve.

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.

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.

PetClaw AI serves as a desktop assistant that operates as a virtual pet within your computer, providing ongoing assistance for various activities including work, education, and everyday tasks. This innovative software functions solely on the user's device, leveraging the open-source OpenClaw framework, and prioritizes user privacy by keeping all data stored locally, ensuring that personal information is never utilized for training purposes or shared without consent. The installation process is straightforward, featuring a one-click setup that automatically handles all configurations, enabling users to start engaging with their AI companion right away. PetClaw facilitates natural voice interactions, allowing users to issue commands, pose inquiries, or delegate intricate tasks, with immediate responses that enhance collaboration in real-time. Its diverse functionalities encompass organizing schedules, composing emails, performing research, coding, and streamlining workflows, while also offering the opportunity for users to impart new skills to the AI. In this way, PetClaw not only serves as a practical assistant but also evolves and adapts to better meet individual user needs.

TinyFish is a web infrastructure platform for developers and AI teams building agents and applications that need to access or operate across the web. The platform includes four connected product surfaces: 1. Search provides agent-optimized web search with current results structured for AI consumption. 2. Fetch extracts clean content from specified URLs and returns it as markdown, JSON, or HTML. It supports dynamic, JavaScript-heavy, and single-page application websites. 3. Browser provides managed cloud Chrome sessions, fingerprinting, session infrastructure, scaling, and browser management. 4. Web Agent takes a goal and a URL, navigates a website, works through filters and pagination, fills forms, authenticates when required, and returns the requested result. 5. Vault and Profiles support Web Agent workflows by securely handling credentials and identity for authenticated website operations. Together, these capabilities allow developers to move from web discovery and content retrieval into complete, multi-step web operations without assembling and maintaining separate infrastructure products.

Qwen3.5-35B-A3B is a member of the Qwen3.5 "Medium" model series, meticulously crafted as an effective multimodal foundation model that strikes a balance between robust reasoning capabilities and practical application needs. Utilizing a Mixture-of-Experts (MoE) architecture, it boasts a total of 35 billion parameters, yet activates only around 3 billion for each token, enabling it to achieve performance levels similar to much larger models while significantly cutting down on computational expenses. The model employs a hybrid attention mechanism that merges linear attention with traditional attention layers, which enhances its ability to handle extensive context and boosts scalability for intricate tasks. As an inherently vision-language model, it processes both textual and visual data, catering to a variety of applications, including multimodal reasoning, programming, and automated workflows. Furthermore, it is engineered to operate as a versatile "AI agent," proficient in planning, utilizing tools, and systematically solving problems, extending its functionality beyond mere conversational interactions. This capability positions it as a valuable asset across diverse domains, where advanced AI-driven solutions are increasingly required.

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.

Happenstance is an innovative platform that utilizes artificial intelligence to enhance people search and relationship intelligence, enabling users to find the right individuals within their networks by simply describing their search in everyday language. By integrating fragmented connections from various sources like email, LinkedIn, Twitter, and team collaborations into a cohesive, searchable database, users can perform detailed searches, such as “a fintech project manager in New York City,” and receive immediate results that highlight the most relevant candidates based on their intent, relationship strength, and context. The platform leverages advanced language models and embedding search technology to comprehend user queries and intelligently rank the findings, thus obviating the need for tedious manual filtering or complex search techniques while providing clear, organized outputs that illustrate how each connection is related. Additionally, it empowers users to broaden their networking potential by merging connections with reliable friends or colleagues, enabling them to uncover warm introductions, overlooked connections, and valuable opportunities that might otherwise go unnoticed. This capability not only enhances professional networking but also fosters collaboration and support within existing relationships, ultimately leading to more successful outcomes.

KAT-Coder represents a cutting-edge AI coding solution that transcends standard autocomplete functionalities by facilitating comprehensive software development processes that involve reasoning, planning, and execution. This system stands as the premier coding model within the KAT ecosystem, specifically tailored for "agentic coding," which allows the model to not only generate code snippets but also to identify problems, suggest solutions, conduct tests, and refine multiple files in a continuous development cycle. It seamlessly integrates into developer environments via API endpoints and proxy layers that are compatible with tools like Claude Code, ensuring that developers can maintain their familiar workflows without needing to alter their interfaces. KAT-Coder employs a sophisticated multi-stage training pipeline that combines supervised fine-tuning with extensive reinforcement learning, which equips it with the ability to grasp programming contexts and tackle intricate tasks effectively. In this way, KAT-Coder not only enhances productivity but also empowers developers to focus more on innovative aspects of their projects.