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panther-mcp

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by PantherWatch
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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

    A4/5.0

    Scored across 13 tools

    Disambiguation5/5

    Each tool targets a distinct resource or lifecycle stage: asset discovery, price data retrieval, backtest execution/status/results, optimization execution/status/results, and portfolio backtest execution/status/results. Run versus optimize versus list versus get operations are clearly separated, and the three status/result pairs are unambiguous.

    Naming Consistency5/5

    All tools follow a consistent verb_prefix + resource pattern such as list_, get_, run_, and optimize_, with the shared tool_ prefix applied uniformly. Related workflows use parallel naming, e.g. get_backtest_status/get_backtest_results and get_optimization_status/get_optimization_results, making the API predictable.

    Tool Count5/5

    13 tools is well-scoped for a backtesting platform, covering asset exploration, single backtests, parameter optimization, portfolio backtests, and result/history retrieval. Each tool serves a distinct purpose without unnecessary sprawl or redundancy.

    Completeness5/5

    The toolset covers the full backtesting lifecycle: discover assets, inspect price data, run and monitor backtests, run and monitor optimizations, run portfolio backtests, retrieve detailed results, and list historical runs. No critical dead ends are apparent for the stated domain.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

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