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Model Context Protocol (MCP) server for Sphinx documentation.

Project description

Package Version PyPI - Status Tests Status Code Coverage Percentage Project License Python Versions

🐲📚 Documentation Search Engine - An intelligent documentation search and extraction tool that provides both a command-line interface for humans and an MCP (Model Context Protocol) server for AI agents. Search across Sphinx and MkDocs sites with fuzzy matching, extract clean markdown content, and integrate seamlessly with AI development workflows.

Key Features ⭐

  • 🔍 Universal Search: Fuzzy, exact, and regex search across documentation inventories and full content

  • 🤖 AI Agent Ready: Built-in MCP server for seamless integration with Claude Code and other AI tools

  • 📖 Multi-Format Support: Works with Sphinx (Furo, ReadTheDocs themes) and MkDocs (Material theme) sites

  • 🚀 High Performance: In-memory caching with sub-second response times for repeated queries

  • 🧹 Clean Output: High-quality HTML-to-Markdown conversion preserving code blocks and formatting

  • 🎯 Auto-Detection: Automatically identifies documentation type without manual configuration

  • 🔌 Extensible: Plugin architecture supports additional documentation formats via extension manager

Installation 📦

Method: MCP Server Configuration

Add as an MCP server in your AI client configuration. For example, in Claude Code’s MCP configuration:

{
  "mcpServers": {
    "librovore": {
      "command": "uvx",
      "args": [
        "librovore",
        "serve"
      ]
    }
  }
}

Method: Download Standalone Executable

Download the latest standalone executable for your platform from GitHub Releases. These executables have no dependencies and work out of the box.

Method: Install Executable Script

Install via the uv tool command:

uv tool install librovore

or, run directly with uvx:

uvx librovore

Or, install via pipx:

pipx install librovore

Method: Install Python Package

Install via uv pip command:

uv pip install librovore

Or, install via pip:

pip install librovore

Examples 💡

Command-Line Interface

Search Python documentation for ‘pathlib’:

librovore query-inventory https://docs.python.org/3 pathlib

Search content with fuzzy matching:

librovore query-content https://fastapi.tiangolo.com "dependency injection"

MCP Server for AI Agents

Start the MCP server for AI agent integration:

librovore serve

The server provides tools for AI agents to search documentation object inventories, search full documentation content with snippets, and get overviews of available documentation.

Use Cases

  • AI Development: Enable Claude Code and other AI agents to search technical documentation

  • Documentation Research: Quickly find API references and usage examples across multiple sites

  • Development Workflows: Access documentation programmatically during development

  • Cross-Reference Search: Find related concepts across different documentation sources

About the Name 📝

The name “librovore” draws from Latin roots meaning “book-devourer” - a fitting metaphor for a tool that consumes and digests documentation across multiple formats:

  • 📚 Anglicized Latin libro- (“book”) + -vore (“devouring”)

  • 🐲 The “Book Wyrm” - traditionally “librovore” is a synonym for “bookworm”, but Claude’s choice of the dragon emoji 🐲 rather than a worm emoji transformed our humble bookworm into a legendary wyrm that devours knowledge and makes it accessible

  • 📖 Both “worm” and “wyrm” share the same Old English origins, so the linguistic evolution fits perfectly

Contribution 🤝

Contribution to this project is welcome! However, it must follow the code of conduct for the project.

Please file bug reports and feature requests in the issue tracker or submit pull requests to improve the source code or documentation.

For development guidance and standards, please see the development guide.

Additional Indicia

GitHub last commit Copier Hatch pre-commit Pyright Ruff PyPI - Implementation PyPI - Wheel

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