Python Docs MCP Server gives AI coding agents local access to the official Python standard library docs. It can look up docs by Python version, return specific sections, and keep answers compact for clients like Claude Desktop, Cursor, and Codex. It runs without API keys or a hosted service.
A Python-based MCP server that enables users to interact with the esa.io API for documentation management. It provides tools for retrieving user information and performing full CRUD operations on articles.
Provides up-to-date Python package manager commands by cross-referencing official pip, poetry, uv, and conda documentation with automatic weekly updates.
Automatically crawls documentation websites, converts them to organized markdown files, and generates condensed cheat sheets. Intelligently categorizes content into tools/APIs and provides local-first access to downloaded documentation.
Provides real-time access to code library documentation and examples through Context7 API integration, enabling AI assistants to retrieve up-to-date technical documentation, code snippets, and best practices for various programming libraries.
Provides AI assistants with specialized tools to interact with NIST's Open Security Controls Assessment Language (OSCAL) framework. It enables agents to retrieve schemas, explore models, and generate valid OSCAL documentation for security compliance automation.
An MCP (Model Context Protocol) server that turns the book Deep Learning with Python (François Chollet) into a searchable knowledge base, so Claude can act as a deep-learning/ML expert grounded in the book's content.
Extracts and stores documentation content from Microsoft Learn and GitHub URLs into PocketBase with full-text search, metadata preservation, and automatic collection management for easy retrieval and organization.
Exposes the structure and documentation of the openreview-py library, enabling LLMs to discover classes, functions, and signatures for accurate code generation. It provides tools for searching the API and retrieving detailed metadata without executing code or making external API calls.
Transforms any GitHub repository into a documentation hub for AI assistants, enabling access to up-to-date documentation and code to eliminate hallucinations. Supports repository-specific and dynamic endpoints with smart search capabilities.
Transforms any GitHub repository or GitHub Pages site into a documentation hub for AI assistants using the Model Context Protocol. It allows AI tools to access real-time code and documentation to prevent hallucinations and provide accurate API usage examples.
An MCP server that retrieves and cleans official documentation for popular AI/Python libraries via web search and LLM processing, exposing a get_docs tool.
Enables hybrid search (BM25 + semantic with RRF) over documentation, with Thai language support. It exposes MCP tools for adding documents and searching via Qdrant and Ollama/OpenAI, using a stateless Streamable HTTP transport.
Rust-powered PDF toolkit over MCP: create, read, and analyze PDFs; extract text and entities for RAG; convert to Markdown; split/merge/rotate/reorder pages; manage form fields and annotations; encrypt documents. Runs locally via uvx oxidize-mcp.