mcp-server-ragdocs
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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.
MCP-server-ragdocs is a server implementation designed to enhance AI responses by integrating relevant documentation context. It utilizes vector-based search and retrieval to process and augment documentation, making it ideal for building documentation-aware AI assistants and creating context-aware tools for developers. The server supports multiple documentation sources and can generate embeddings locally using Ollama or through OpenAI. It offers semantic search capabilities and real-time context augmentation for language models, making it a powerful tool for augmenting existing knowledge bases.
Features
- Vector-based documentation search and retrieval
- Support for multiple documentation sources
- Local or OpenAI embeddings generation
- Semantic search capabilities
- Automated documentation processing
