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kalicyh

MCP RAG

by kalicyh
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Python
Hybrid

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    • MCP RAG

      fastmcp-me
      F
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      B
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      A RAG-based knowledge base system supporting document processing, semantic search, and intelligent Q\&A with multiple AI model integrations.
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    • MCP Knowledge Base

      july090
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      D
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      A local knowledge base system based on ChromaDB that supports automatic chunking, vector storage, and efficient similarity retrieval of txt and pdf documents, with MCP protocol support allowing AI assistants to directly access knowledge management functions.
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    • local-kb

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      Enables AI tools to search and manage a private local knowledge base via MCP or HTTP, using local Chinese semantic retrieval without sending data externally.
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    • FastGPT Knowledge Base MCP

      boleyn
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      quality
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      Intelligent knowledge base management tool that enables searching, browsing, and analyzing documents across multiple datasets with smart document analysis capabilities.
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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A3.9/5.0

    Scored across 10 tools

    Disambiguation5/5

    Each tool has a clear, distinct purpose: querying with/without filters, learning from files or text, and various statistics and maintenance operations. There is no functional overlap.

    Naming Consistency4/5

    Tool names follow a consistent verb_noun pattern in snake_case, e.g., ask_rag, learn_document, get_knowledge_base_stats. The only deviation is 'clear_embedding_cache_tool' which includes an unnecessary 'tool' suffix.

    Tool Count5/5

    With 10 tools covering querying, learning, statistics, and maintenance, the set is well-scoped for a RAG knowledge base server. No tool is redundant, and the number is appropriate for the domain.

    Completeness3/5

    The tools cover essential operations (add, query, manage, maintain), but lack delete or list/update for documents, which are common for a full lifecycle. The gaps are minor but notable.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources