mcp-server-ragdocs
20
This project is an MCP server designed to enhance AI tools by providing vector search capabilities for documentation retrieval and processing. It allows integrations with various embeddings providers for semantic search and context augmentation.
Overview
An MCP server implementation that provides tools for retrieving and processing documentation through vector search. This enhances AI responses with relevant documentation and enables developers to create context-aware tools.
Usage
- 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
Features
- Vector-based documentation search and retrieval
- Multiple documentation sources
- Local and OpenAI embeddings support
- Semantic search capabilities
- Automated documentation processing
- Real-time context augmentation for LLMs
Tools
- search_documentation: Search stored documentation.
- list_sources: List all indexed documentation.
- extract_urls: Extract URLs from webpages.
- remove_documentation: Remove documentation sources.
- list_queue: List queued documentation.
- run_queue: Process URLs in the queue.
- clear_queue: Clear processing queue.