A Model Context Protocol server that fetches up-to-date, version-specific documentation and code examples from libraries directly into LLM prompts, helping developers get accurate answers without outdated or hallucinated information.
Provides a local MCP server for searching and retrieving documentation from 22+ open-source projects, enabling AI coding assistants to access up-to-date docs without network dependency.
A local-only MCP server that provides AI coding agents with up-to-date documentation for specific libraries or tools during feature implementation, including search tools, multi-version support, and user-defined library entries.
MCP server that enables coding agents to retrieve project context, semantically search indexed documentation, and read specific documents from registered repositories.
Local MCP server that indexes documentation from URLs/files into a vector database, enabling coding agents to search and use up-to-date library and API documentation.
A local-first MCP server that indexes code repositories and enables AI assistants to search, fetch, and navigate code using BM25 hybrid retrieval, supporting common languages and tools like Codex and ChatGPT.
Enables AI agents to locally search, query, and understand codebases with token-efficient context, dependency graphs, history, architecture diagrams, and metrics through MCP.
