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Description

Rafter is a security scanning platform designed with developers in mind, enabling the identification and resolution of vulnerabilities in GitHub repositories through a simple click or command. Its integration is smooth via a web-based dashboard, command-line interface, or REST API, allowing for the scanning of JavaScript, TypeScript, and Python code to uncover various issues such as exposed API keys, SQL injection vulnerabilities, XSS flaws, insecure dependencies, hardcoded credentials, and weaknesses in authentication. The results are organized into three clear categories: “Errors,” “Warnings,” and “Improvements,” each providing in-depth explanations, specific code locations, remediation guidance, and formatted prompts that can be easily utilized in AI coding tools. Users can access findings in both JSON and Markdown formats, automate scans as part of CI/CD pipelines, and seamlessly integrate scan results into their existing workflows. Rafter’s flexible approach accommodates no-code, low-code, and full-code environments, ensuring that developers can implement proactive security measures early in the software development process, making it not only effortless but also scalable as project requirements grow. This adaptability allows teams to maintain a robust security posture while focusing on delivering high-quality software efficiently.

Description

Tabstack is a managed web extraction, research, and automation API designed to help developers build live-web features without maintaining browser infrastructure or scraping pipelines. Users can send a URL, structured schema, research question, or plain-language task and receive clean data, cited research, or completed web actions from a single API call. The platform includes endpoints for extracting schema-matched JSON, converting pages into clean Markdown, generating structured outputs, running cited research agents, and automating browser tasks. Tabstack handles the reasoning, rendering, schema enforcement, browser execution, and orchestration behind the scenes so teams can focus on building products instead of managing extraction systems. Its research endpoint reads the live web, selects sources, synthesizes answers, and returns citations on claims, making it useful for trustworthy research agents. Its automation endpoint can navigate, click, fill forms, and complete multi-step workflows on third-party sites, with interactive pauses when human input is needed. Tabstack also supports TypeScript and Python SDKs, MCP integration, CLI access, and streaming responses over SSE. Developers can use it for lead enrichment, competitive monitoring, knowledge base ingestion, workflow automation, booking flows, product data extraction, and in-app research. With privacy controls, no model training on user data, and plans ranging from free credits to enterprise quotas, Tabstack gives teams a practical backend for AI agents that need to understand and act on the web.