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karaage0703

MCP RAG Server

by karaage0703

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    • A
      license
      A
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      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.
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      AGPL 3.0
    • A
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      Not graded
      quality
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      maintenance
      A Retrieval Augmented Generation system that enables AI assistants to perform semantic searches and manage document indices for markdown files. It supports PostgreSQL with pgvector and integrates both Google Gemini and Ollama for intelligent embedding generation.
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    • 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.
      3
      Apache 2.0
    • A
      license
      A
      quality
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      Enables AI agents to ingest documentation from websites or local files and perform semantic search over the indexed content using pgvector-backed embeddings.
      5
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      Enables semantic search and question-answering over uploaded documents using vector embeddings and Google AI. Supports document organization with tags, section-aware queries, and hierarchical markdown structure preservation.
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