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MCP Code Mode

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.

    Resources