An MCP server that crawls API documentation websites and exposes their content to AI models, enabling them to search, browse, and reference API specifications.
A lightweight, zero-config MCP server that makes documentation and API specifications instantly accessible to AI models using the llms.txt standard. It enables searching and retrieving full documentation, OpenAPI, and AsyncAPI specs without requiring a complex RAG infrastructure or vector database.
An MCP server that crawls and parses OpenAPI JSON or Swagger UI URLs to provide concise endpoint summaries. It enables LLMs to discover and interact with API interfaces by extracting methods, paths, and operation IDs from documentation sources.
An MCP server that fetches real-time documentation for popular libraries like Langchain, Llama-Index, MCP, and OpenAI, allowing LLMs to access updated library information beyond their knowledge cut-off dates.
A generic MCP server that dynamically exposes any OpenAPI-documented REST API to LLMs by auto-discovering endpoints. It provides tools for exploring API capabilities and making authenticated requests directly through natural language interfaces.