sanderkooger-mcp-server-ragdocs
Provides vector-based semantic search and real-time context augmentation for AI assistants by retrieving and processing documentation from multiple sources using Model Context Protocol.
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Base URL for Ollama service (used when EMBEDDINGS_PROVIDER is 'ollama')
http://127.0.0.1:11434API key for authenticating with Qdrant (if applicable)
Provider to use for generating embeddings
ollamaAPI key for OpenAI (required when EMBEDDINGS_PROVIDER is 'openai')
URL of your Qdrant vector database instance
Security Notice
Your environment variables and credentials are securely stored and encrypted. LangDB never shares these configuration values with third parties.
Provides vector-based semantic search and real-time context augmentation for AI assistants by retrieving and processing multiple documentation sources through the Model Context Protocol.
7 toolsAdded May 30, 2025
Provides vector-based semantic search and real-time context augmentation for AI assistants by retrieving and processing multiple documentation sources through the Model Context Protocol.
Added May 30, 2025
Provides tools for retrieving, managing, and processing documentation via vector search to enhance AI assistant responses with relevant, context-aware information using the Model Context Protocol.
Added May 30, 2025
Provides up-to-date, version-aware documentation indexing and advanced semantic search via the Model Context Protocol to enhance AI coding assistants with accurate, reliable, and private access to official code references from multiple sources.
Added May 29, 2025
Model Context Protocol server offering retrieval-augmented generation with semantic document search, management, and vector similarity using Qdrant and Ollama or OpenAI embeddings.
Added May 30, 2025