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mcp-rag-local

by renl
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Python
Local

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    Deploy Server
    Context All Your Agents Can ShareAgents share what they learn, hand off work, and hold it when you switch models. Start with 5 GB free.fulcradynamics.comAd

    TDQS

    B3.3/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: greeting, memorizing text, memorizing multiple texts, memorizing PDF files, and retrieving similar texts. No ambiguity between tools.

    Naming Consistency5/5

    All tool names follow a consistent snake_case pattern with verb_noun or verb_adjective_noun structure (e.g., greet_user, memorize_text, remember_similar_texts).

    Tool Count4/5

    5 tools is appropriately scoped for a simple RAG local server, covering core operations without being overwhelming. Slightly on the low side but reasonable.

    Completeness3/5

    The tool set provides storage and retrieval but lacks update, delete, or listing operations, which are common in memory systems. This could limit agent capabilities.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

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