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Related Servers

Alternatives to mcp-agentic-rag

No user-submitted related servers found.

    Related Servers

    • A
      license
      A
      quality
      C
      maintenance
      Exposes a RAG document-search API as MCP tools (rag_health, rag_ingest, rag_query), enabling agents to index and search markdown documents with cited results through natural language.
      3
      MIT
    • F
      license
      Not graded
      quality
      C
      maintenance
      Enables local RAG orchestration with MCP, providing context retrieval, in-memory text ingestion, explicit tool invocation, and transport-neutral tool discovery.
      -
    • F
      license
      Not graded
      quality
      B
      maintenance
      Exposes a Retrieval-Augmented Generation pipeline as MCP tools, allowing users to index documents and query them through any MCP-compatible client like Claude or IDEs.
      -
    • A
      license
      A
      quality
      C
      maintenance
      Exposes hybrid retrieval (dense embeddings + BM25 + RRF) and document operations (search, fetch, rerank) as MCP tools, using Qdrant and OpenAI embeddings for local or server mode.
      3
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      Provides tools for ingesting documents into a local vector database and retrieving relevant information via semantic search, enabling retrieval-augmented generation for MCP clients.
      6
      -
    • A
      license
      A
      quality
      A
      maintenance
      Provides read-only MCP tools for searching and asking over private documents via a local RAG service (reed), returning ranked passages with citations while keeping data on the machine.
      4
      Apache 2.0

    TDQS

    C2.7/5.0

    Scored across 3 tools

    Disambiguation4/5

    The two query tools are distinguished by the fallback feature, and seed is clearly separate. Some confusion possible but descriptions help.

    Naming Consistency5/5

    All tools follow a consistent snake_case verb_noun pattern, making naming predictable and logical.

    Tool Count3/5

    With only 3 tools, the set feels minimal but is within acceptable bounds for a simple RAG server. However, missing management tools make it slightly thin.

    Completeness2/5

    The toolset lacks capabilities to update, delete, or list documents, which are essential for a complete RAG knowledge base management. This is a significant gap.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues