A version-aware cache for web research that stores and serves documentation references, preventing models from re-researching the same topics across sessions.
A self-hosted MCP server that crawls, indexes, and searches documentation from any website locally, including private sites requiring authentication. It provides hybrid search capabilities and local embedding generation to maintain privacy while keeping AI assistant knowledge up to date.
Provides AI coding assistants with on-demand access to component specs, test scenarios, accessibility requirements, and build guides from the Web UI Component Specification.
Delivers curated documentation, quickstart commands, and stack recommendations for modern full stack web development through MCP-enabled AI assistants.
Enables intelligent navigation and extraction of documentation from websites, allowing Amazon Q to automatically discover relevant pages, extract clean content, and retrieve code examples from web documentation.
Enables retrieval and cleaning of official documentation content for popular AI/Python libraries (uv, langchain, openai, llama-index) through web scraping and LLM-powered content extraction. Uses Serper API for search and Groq API to clean HTML into readable text with source attribution.
Enables web page scraping via Jina reader API and searching FastMCP documentation using minsearch. Supports fetching markdown content from URLs and querying indexed documentation files.
Enables AI assistants to search and access arXiv papers through a Model Context Protocol interface, allowing for paper search, download, listing, and reading functionality.
Pure Node.js MCP server that renders and validates PlantUML diagrams with zero Java and zero external server, powered by TeaVM. Exposes render_diagram, check_syntax and diagram_explain — just run npx @plantuml/mcp-js.
Enables natural language interaction with the Korean Personal Information Protection Act (PIPA) through 37 MCP tools that search, compare, analyze, and verify legal texts, official guidelines, and consulting cases from authoritative sources.
Provides LLMs with up-to-date, version-specific documentation and code examples directly from library sources, eliminating outdated training data and hallucinated APIs by fetching current documentation at prompt time.
Enables AI models to search and retrieve offline security knowledge from over 20 curated sources including HackTricks, PayloadsAllTheThings, and OWASP guides, via the Model Context Protocol.