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Pramod-Potti-Krishnan

Document Retrieval MCP Server

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    • A
      license
      A
      quality
      B
      maintenance
      Enables ingestion and semantic search over text documents using PostgreSQL + pgvector and OpenAI-compatible embeddings, allowing any LLM agent to retrieve relevant chunks for grounded answers.
      4
      AGPL 3.0
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables MCP-capable AI to perform read-only semantic search over a local document corpus stored in Postgres with pgvector, using mxbai-embed-large embeddings and optional reranking for confidence-gated results.
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    • A
      license
      Not graded
      quality
      B
      maintenance
      Connects to a PostgreSQL database (pgvector) to perform semantic retrieval via the search_documents tool, returning raw document snippets for LLM synthesis.
      1
      GPL 3.0
    • A
      license
      B
      quality
      D
      maintenance
      Enables retrieval-augmented generation by embedding queries with a chosen provider (e.g., OpenAI) and searching supported vector stores (Pinecone, pgvector) to return relevant content.
      1
      Apache 2.0
    • A
      license
      Not graded
      quality
      D
      maintenance
      Enables semantic search across text documents using vector embeddings stored in PostgreSQL. Provides multiple search modalities including semantic similarity, question/answer, and style-based search through a retrieval-augmented generation system.
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