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    • A
      license
      Not graded
      quality
      D
      maintenance
      Enables quantitative trading research by providing tools to backtest strategies, list market datasets, review forward-test logs, and search previously rejected hypotheses, all through an MCP interface.
      MIT
    • F
      license
      B
      quality
      C
      maintenance
      Enables financial data retrieval, company context, market information, financial modelling, and valuation through MCP tools, with a deterministic sample provider for testing before connecting live data sources.
      15
      -
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI agents to run a full quant research workflow over MCP: pulling data, authoring and backtesting strategies, running statistical validation and risk checks, and recording findings for future sessions.
      1
      MIT
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents and backend workflows to access standardized multi-market financial data, technical indicators, fundamentals, news, filings, money flow, and CSV/JSON exports through MCP tools and HTTP endpoints.
      -
    • A
      license
      B
      quality
      C
      maintenance
      Provides a suite of MCP tools for evidence-grounded investment research, including time-bounded search of reports and news, thesis verification against subsequent events, market response calculations, and generation of validated research briefs.
      9
      MIT
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents and backend services to query market data, technical indicators, fundamentals, money flow, news, and filings across A-shares, US equities, ETFs, indices, and crypto. Capabilities are exposed both as MCP tools and as an HTTP API, including CSV/JSON export endpoints suited to code-executing agents.
      -

    TDQS

    A4.2/5.0

    Scored across 8 tools

    Disambiguation5/5

    Each tool serves a unique, clearly delineated role: capabilities for introspection, resolve for entity mapping, discover for field search, fetch for data retrieval, events for timeline data, backtest for running strategies, benchmark for performance comparison, and status for system health. No two tools overlap in their core function.

    Naming Consistency5/5

    All tool names are single lowercase words (capabilities, resolve, discover, fetch, events, backtest, benchmark, status), following a minimal and uniform naming convention with no mixing of styles such as underscores or camelCase.

    Tool Count5/5

    8 tools provide a well-scoped interface for quantitative finance research, covering the full workflow from exploration to validation without unnecessary redundancy or excessive granularity.

    Completeness5/5

    The set provides a complete lifecycle: capabilities and discover facilitate exploration, resolve handles entity identification, fetch retrieves data, events offers time-series events, backtest tests strategies, benchmark compares against factors, and status monitors the system. There are no evident gaps for the stated purpose.

    Maintenance

    ActivityActive
    ResponsivenessResponsive