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Alternatives to futures-kb

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    Related Servers

    • A
      license
      Not graded
      quality
      B
      maintenance
      Provides AI agents with standard MCP tool calls to run A-share market research workflows—macro analysis, daily review generation, strategy backtesting, watchlist scanning, stock analysis, and risk monitoring—while preserving manual confirmation for trade decisions.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to perform quantitative research and backtesting for China A-shares and futures, including data fetching, backtesting, factor analysis, and experiment tracking through MCP tools.
      2
      Apache 2.0
    • F
      license
      Not graded
      quality
      D
      maintenance
      Provides web search, page fetching, and A-stock data access (financial reports, announcements, research reports, penalties, IR meetings) via MCP tools.
      -
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents and backends to query A-share, US equity, ETF, index, and crypto market data, compute technical indicators, retrieve fundamentals, news, filings, money flow, and export CSV/JSON for code workflows through MCP tools and HTTP APIs.
      -
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to query A-share, US equity, ETF, index, and crypto market data and run technical analysis, fundamentals, money-flow, news, and SEC/A-share filing tools through a unified MCP interface. It also supports CSV/JSON code-export and can be deployed as a standalone HTTP API.
      -
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents and backends to query A-share, US equity, ETF, index, and crypto market data with technical indicators, fundamentals, money flow, news search, and SEC/A-share filings through MCP tools. Also exposes CSV/JSON code-export endpoints so script-driven agents can pull data without bloating model context.
      -

    TDQS

    A3.5/5.0

    Scored across 7 tools

    Disambiguation5/5

    Each tool has a clearly distinct responsibility: market context generation, manual data submission, crawler execution, report persistence, report listing, report reading, and research search. There is no meaningful overlap or ambiguity between tool purposes.

    Naming Consistency3/5

    The report_* tools follow a noun-verb pattern (save/list/read), and manual_data_submit is similar, but daily_report_context, market_run_crawler, and research_search do not follow the same convention. This mixed structure makes the naming pattern less predictable.

    Tool Count5/5

    Seven tools is a well-scoped size for a futures knowledge base server, covering data ingestion, crawling, reporting, and research without unnecessary bloat. Each tool contributes a distinct capability.

    Completeness4/5

    The tool set covers the main workflow: submit/ingest data, generate report context, save/list/read reports, and search research. Minor gaps exist, such as no direct way to query or delete submitted data and no explicit report deletion, but the core lifecycle is otherwise supported.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues