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GraphRAG Llama Index MCP Server

by T-NhanNguyen
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Python
Hybrid

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    TDQS

    A4.1/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose with no ambiguity: explore_entity_graph is for graph traversal from a specific entity, get_corpus_stats is for corpus-level statistics, and search is for querying the knowledge base with three distinct modes (keyword_lookup, entity_connections, thematic_overview). The tools do not overlap in functionality.

    Naming Consistency4/5

    The tool names follow a consistent snake_case pattern (explore_entity_graph, get_corpus_stats, search), but 'search' is a generic verb compared to the more descriptive 'explore' and 'get', which is a minor deviation. Overall, the naming is predictable and readable.

    Tool Count3/5

    With only 3 tools, the server feels thin for a GraphRAG system, as it might lack operations like updating or managing the knowledge base. However, the tools cover core query and exploration functions, making it borderline appropriate for basic usage.

    Completeness4/5

    The tool surface covers key operations for querying and exploring a GraphRAG knowledge base, including graph traversal, corpus statistics, and multi-mode search. Minor gaps exist, such as no tools for adding or modifying data, but agents can work around this for read-only analysis.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources