arabold/docs-mcp-server
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Docs MCP Server is a tool that provides a personal, always-current knowledge base for AI by indexing third-party documentation from various sources, offering version-aware search tools via the Model Context Protocol (MCP).
Grounded Docs: Your AI's Up-to-Date Documentation Expert
Docs MCP Server solves the problem of AI hallucinations and outdated knowledge by providing a personal, always-current documentation index for your AI coding assistant. It fetches official docs from websites, GitHub, npm, PyPI, and local files, allowing your AI to query the exact version you are using.
✨ Why Grounded Docs MCP Server?
The open-source alternative to Context7, Nia, and Ref.Tools.
- ✅ Up-to-Date Context: Fetches documentation directly from official sources on demand.
- 🎯 Version-Specific: Queries target the exact library versions in your project.
- 💡 Reduces Hallucinations: Grounds LLMs in real documentation.
- 🔒 Private & Local: Runs entirely on your machine; your code never leaves your network.
- 🧩 Broad Compatibility: Works with any MCP-compatible client (Claude, Cline, etc.).
- 📁 Multiple Sources: Index websites, GitHub repositories, local folders, and zip archives.
- 📄 Rich File Support: Processes HTML, Markdown, PDF, Word (.docx), Excel, PowerPoint, and source code.
🚀 Quick Start
1. Start the server (requires Node.js 22+):
npx @arabold/docs-mcp-server@latest
2. Open the Web UI at http://localhost:6280 to add documentation.
3. Connect your AI client by adding this to your MCP settings (e.g., claude_desktop_config.json):
{
"mcpServers": {
"docs-mcp-server": {
"type": "sse",
"url": "http://localhost:6280/sse"
}
}
}
See for VS Code (Cline, Roo) and other setup options.
Alternative: Run with Docker
docker run --rm \
-v docs-mcp-data:/data \
-v docs-mcp-config:/config \
-p 6280:6280 \
ghcr.io/arabold/docs-mcp-server:latest \
--protocol http --host 0.0.0.0 --port 6280
🧠 Configure Embedding Model (Recommended)
Using an embedding model is optional but dramatically improves search quality by enabling semantic vector search.
Example: Enable OpenAI Embeddings
OPENAI_API_KEY="sk-proj-..." npx @arabold/docs-mcp-server@latest
See for configuring Ollama, Gemini, Azure, and others.
📚 Documentation
Getting Started
- : Detailed setup guides for Docker, Node.js (npx), and Embedded mode.
- : How to connect Claude, VS Code (Cline/Roo), and other MCP clients.
- : Using the Web UI, CLI, and scraping local files.
- : Full reference for config files and environment variables.
- : Configure OpenAI, Ollama, Gemini, and other providers.
Key Concepts & Architecture
- : Standalone vs. Distributed (Docker Compose).
- : Securing your server with OAuth2/OIDC.
- : Privacy-first usage data collection.
- : Deep dive into the system design.
🤝 Contributing
We welcome contributions! Please see for development guidelines and setup instructions.
License
This project is licensed under the MIT License. See for details.
