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django-chainsaw-mcp

by syrian963
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    TDQS

    A3.7/5.0

    Scored across 37 tools

    Disambiguation3/5

    Several tools cluster around related concerns—N+1 queries (defeated_prefetches, unused_eager_loading, serializer_nplusone, sqlalchemy_nplusone, find_n_plus_one, scan_templates, queries_in_loops) and API exposure (api_contract, serializer_exposure, open_endpoints, amplification, fastapi_exposure). The individual descriptions do differentiate them, but an agent assembling a workflow would need to read carefully to avoid selecting a near-miss tool.

    Naming Consistency3/5

    All names are snake_case and largely domain-specific, but they mix grammatical forms: noun phrases (project_info, endpoint_cost, missing_indexes), past participles (bypassed_effects, multiplied_aggregates), and bare verbs (check, explain_model). Related concepts are phrased inconsistently (find_n_plus_one vs serializer_nplusone vs defeated_prefetches), so the convention is readable but not predictable.

    Tool Count2/5

    37 tools is well beyond the 'heavy' range and several could be consolidated (notably the N+1 cluster and the exposure/serializer cluster). The broad framework coverage (Django, DRF, FastAPI, SQLAlchemy, Celery) explains part of the size, but it makes the surface feel bloated rather than focused.

    Completeness4/5

    For a static analysis/linter server, the surface is remarkably broad: migrations, serializers, security, tenant-scoping, deletion cascades, signals, datetime, indexes, aggregates, and async/Celery pitfalls are all covered. Minor gaps exist—there is no direct MCP tool to apply fixes or manage snapshots beyond check and suggest_fixes—but no core workflow feels like a dead end.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources