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CodeRAG

CodeRAG

by azraf122312
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Python
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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

    A4.1/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool targets a distinct phase of the RAG workflow: indexing, status, searching, context retrieval, and impact analysis. search_code and get_context both retrieve code, but get_context explicitly adds citations and call-graph expansion, so they are clearly separated.

    Naming Consistency4/5

    All names use snake_case and follow a command-like style. However, status is a bare noun rather than verb_noun, and impact_radius is a noun phrase while others start with verbs (index, search, get). Minor deviations but overall predictable.

    Tool Count5/5

    Five tools is well-scoped for a code RAG server: one tool to build the index, one for health/size, one for basic search, one for context-rich retrieval, and one for dependency impact. No unnecessary tools.

    Completeness4/5

    The core lifecycle is covered: index creation, search, context extraction, and impact analysis. Missing explicit delete/re-index or list available repositories, but these are minor gaps for a focused RAG use case.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources