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Alternatives to btmcp

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    Related Servers

    • A
      license
      Not graded
      quality
      C
      maintenance
      Local-first backtesting engine with built-in overfitting detection (PBO, deflated Sharpe, bootstrap CI, walk-forward) and a native MCP server for AI agents to validate trading strategies.
      4
      Apache 2.0
    • A
      license
      A
      quality
      D
      maintenance
      Enables AI assistants to backtest trading strategies described in plain English, providing access to market data, technical indicators, and comprehensive performance reports.
      13
      1
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      MCP server for natural-language daily stock/ETF strategy backtesting. It provides constrained tools for strategy specification, data validation, queue-based backtests, and verifiable result artifacts.
      2
      Apache 2.0
    • F
      license
      Not graded
      quality
      B
      maintenance
      Provides deterministic A-share market snapshots and immutable strategy versions for short-term review, exposing verified daily reports via MCP without order or account management.
      -
    • A
      license
      Not graded
      quality
      D
      maintenance
      Enables backtesting of limit-order strategies on Polymarket's BTC 5-minute markets using historical data, with tools to browse markets, get price series, and run simulations.
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables market-data analysis and quantitative research over a local Parquet lake with tools for bars, indicators, scans, backtests, and safe SQL queries.
      MIT

    TDQS

    A4/5.0

    Scored across 10 tools

    Disambiguation4/5

    Most tools have clearly distinct purposes: listing symbols, profiling series, fetching bars, running/validating backtests, and inspecting runs/trades. The only mild overlap is between describe_series and get_bars, since both return summary statistics about price data, but their different scopes (single-series profile vs. multi-symbol window aggregates) make the boundary clear enough.

    Naming Consistency5/5

    All tool names follow a consistent snake_case verb_noun pattern: list_symbols, describe_series, get_bars, validate_strategy, run_backtest, explain_trades, publish_run_report. There is no mixing of camelCase, inconsistent verbs, or vague names like 'process' or 'helper'.

    Tool Count5/5

    Ten tools is well-scoped for a backtesting/data-analysis server. Each tool covers a distinct stage of the workflow: data discovery, series inspection, bar data, news, strategy validation, backtest execution, run retrieval, comparison, trade explanation, and publishing.

    Completeness4/5

    The core backtesting workflow is well covered: explore data, validate a strategy, run it, inspect results, compare runs, explain trades, and publish a report. A minor gap is the lack of a list_runs or similar discovery tool, so an agent without prior run IDs cannot enumerate completed runs, though this is workable since run_backtest returns IDs and links.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues