What environment variables are required?
You need `OPENAI_API_KEY` for embeddings generation, `QDRANT_URL` for your Qdrant vector database instance, and `QDRANT_API_KEY` for authenticating with Qdrant.
RAG Documentation MCP Server
@hannesrudolph
Basic information
About RAG Documentation MCP Server
An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.
RAG Documentation MCP Server config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"rag-docs": {
"command": "npx",
"args": [
"-y",
"@hannesrudolph/mcp-ragdocs"
],
"env": {
"OPENAI_API_KEY": "",
"QDRANT_URL": "",
"QDRANT_API_KEY": ""
}
}
}
}RAG Documentation MCP Server tools
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Overview
What is RAG Documentation MCP Server?
An MCP server that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context. It supports multiple documentation sources and uses semantic search to find relevant excerpts.
How to use RAG Documentation MCP Server?
Install the server via npx and add it to your claude_desktop_config.json with the required environment variables (OPENAI_API_KEY, QDRANT_URL, QDRANT_API_KEY). Once configured, use the provided tools such as search_documentation to query indexed documentation or extract_urls to add new sources.
Key features of RAG Documentation MCP Server
- Vector-based documentation search and retrieval
- Support for multiple documentation sources
- Semantic search capabilities
- Automated documentation processing
- Real-time context augmentation for LLMs
Use cases of RAG Documentation MCP Server
- Enhancing AI responses with relevant documentation
- Building documentation-aware AI assistants
- Creating context-aware tooling for developers
- Implementing semantic documentation search
- Augmenting existing knowledge bases
Frequently asked questions
How do I search documentation?
Use the `search_documentation` tool with a natural language query and an optional `limit` (1–20, default 5) to receive ranked excerpts with context.
How can I add new documentation sources?
Use the `extract_urls` tool on a public webpage to find hyperlinks, optionally adding them to the processing queue. Then run the `run_queue` tool to index them.
How do I remove documentation?
Use the `remove_documentation` tool with an array of exact URLs. Removal is permanent and affects future search results.
Can I monitor the processing queue?
Yes, use `list_queue` to see pending URLs and `clear_queue` to remove all pending items immediately.
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