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  • MCP RAG with ChromaDB

    CyprianFusi
    A
    license
    -
    quality
    D
    maintenance
    Provides retrieval-augmented generation (RAG) capabilities by ingesting various document formats into a persistent ChromaDB vector store. It enables semantic search and retrieval using either OpenAI or Ollama embeddings for processing local files, directories, and URLs.
    1
    MIT

  • nacre

    nacre-work
    A
    license
    -
    quality
    A
    maintenance
    Provides a self-hosted knowledge index with document-level permissions, enabling AI agents to retrieve exactly the documents they are authorized to see via MCP. Supports OAuth 2.1, custom embedding models, and runs inside your network.
    31
    Apache 2.0

  • Tiny Chat

    to-aoki
    A
    license
    D
    quality
    C
    maintenance
    A lightweight RAG system that provides an MCP server for searching and interacting with vector-based knowledge bases. It enables users to perform retrieval-augmented generation and search across Qdrant collections through a standardized interface.
    1
    2
    MIT

  • docs-mcp

    globalion
    A
    license
    -
    quality
    B
    maintenance
    Upload documents (Word, Excel, PDF, PowerPoint) to a vector RAG store and perform semantic search with page-level citations. Queries are free; ingestion costs credits at break-even pricing.
    MIT

  • docs-mcp

    Shreyas-Profile
    A
    license
    -
    quality
    B
    maintenance
    Upload Word, Excel, PDF, or PowerPoint documents to a vector RAG store with vision-model extraction, then search semantically and retrieve chunks with page numbers for precise citations.
    MIT

  • ickyMCP

    dl1683
    A
    license
    -
    quality
    D
    maintenance
    RAG-powered document search server that enables semantic search across large collections of legal and business documents (PDF, Word, Excel, PowerPoint) using local embeddings with no API costs.
    4
    MIT
  • Tribal by tribal-memory

    Tribalofficial

    tribal-memory
    F
    license
    A
    quality
    A
    maintenance
    Semantic memory for AI builders: capture the tacit engineering know-how that never reaches your docs, recall it the moment it applies. Built in Rust on Postgres and pgvector.
    10
    9

  • quarry

    punt-labs
    A
    license
    A
    quality
    A
    maintenance
    Enables local semantic search over documents and code for Claude Code and Claude Desktop, running entirely offline with local embeddings and vector storage.
    11
    3
    MIT

  • MCP RAG

    kalicyh
    F
    license
    A
    quality
    C
    maintenance
    Intelligent knowledge base system that enables users to process documents in 25+ formats, perform semantic search and Q\&A through vector retrieval. Supports multiple AI models including OpenAI and DouBao with local processing capabilities.
    10
    6

  • search-docs

    otolab
    A
    license
    A
    quality
    A
    maintenance
    Enables AI agents to search local Markdown documents using natural language, with automatic indexing and section-level retrieval.
    9
    2
    1
    MIT

  • qdrant-llamaindex-mcp-server

    azhang
    A
    license
    B
    quality
    D
    maintenance
    An MCP server for querying and managing LlamaIndex documents stored in Qdrant vector databases, with automatic embedding model detection and extensive tools for search, retrieval, and collection management.
    17
    Apache 2.0