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MCP Code Mode

by anaseqal
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    TDQS

    A4.2/5.0

    Scored across 9 tools

    Disambiguation5/5

    Each tool has a clear and distinct purpose. run_python and run_python_stream are differentiated by streaming vs. non-streaming execution. run_with_retry adds retry logic. Learning tools (add_learning, record_semantic_failure) handle different failure types. configure, get_learnings, get_system_context, and pip_install are all unique and unambiguous.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case, e.g., add_learning, run_python, get_system_context. There are no deviations or mixed conventions.

    Tool Count5/5

    With 9 tools, the set is well-scoped for a code execution MCP server. It covers execution, learning, configuration, context retrieval, and package management without redundancy or gaps.

    Completeness4/5

    The tool surface covers core workflows: code execution (with variants), error/semantic learning, configuration, system context, and package installation. Minor gaps exist (e.g., no tool to delete or update learnings), but overall it's nearly complete for the stated purpose.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources