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quant-research-mcp

by FlawlessByte
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Python
Remote

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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

    A4.3/5.0

    Scored across 13 tools

    Disambiguation5/5

    Each tool targets a distinct operation: analysis, backtesting, event checking, indicator computation, method description, regime detection, news fetching, method listing, market context, portfolio risk, decision scoring, and universe screening. No two tools have overlapping purposes.

    Naming Consistency5/5

    All tools follow a consistent 'quant_verb_noun' pattern (e.g., quant_analyze_setup, quant_screen_universe). The naming is predictable and clear, with no mixing of conventions.

    Tool Count5/5

    13 tools is well-scoped for a quantitative research server. Each tool serves a necessary function in the workflow, from analysis to risk management, without being bloated or sparse.

    Completeness4/5

    The tool set covers the core pipeline: screening, analysis, backtesting, risk assessment, and decision scoring. Minor gaps exist (e.g., no direct data export or charting), but these are not essential for the stated purpose of paper-backed trading research.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources