Skip to main content
Glama
Dor1Toes

BackTest_MCP

by Dor1Toes
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Related Servers

Alternatives to BackTest_MCP

No user-submitted related servers found.

    Related Servers

    • diepi-mcp

      elonmaskhair-prog
      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.
      1
      Apache 2.0
    • backtest360-mcp by Backtest360

      backtest360-mcpofficial

      Backtest360
      A
      license
      A
      quality
      D
      maintenance
      MCP server that exposes the Backtest360 backtesting engine API as tools, enabling AI agents to conversationally discover indicators, build and validate strategies, run backtests, and read results.
      14
      60 PyPI
      MIT

    • Litmus

      Spectrexf
      A
      license
      Not graded
      quality
      C
      maintenance
      An MCP server that lets an AI agent backtest, risk-check, and audit trading strategies, determining if a strategy is overfit or actually works.
      MIT

    • StocksMCP

      pawanthanay
      F
      license
      Not graded
      quality
      D
      maintenance
      AI-powered stock research MCP server with real-time data, CRUD operations, and interactive dashboard for fundamental analysis and comparisons.
      -
    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

    A4.4/5.0

    Scored across 8 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: data fetching, cache listing, running backtests, retrieving results, listing jobs, generating reports, accessing artifacts, and scanning live signals. No two tools overlap in function, even though several relate to backtests but target different aspects (results vs artifacts vs jobs).

    Naming Consistency4/5

    The naming follows a verb_noun pattern with prefixes like get_, list_, run_, generate_, and scan_. The mix of get_backtest_result and get_backtest_artifacts vs list_backtest_jobs and list_cached_symbols is syntactically consistent, though get vs list could be unified. Overall it is predictable and readable.

    Tool Count5/5

    Eight tools is ideal for a backtesting MCP server. The scope is tightly focused on data retrieval, backtest execution, result inspection, artifact access, reporting, and live signal generation—each tool addresses a distinct step in the workflow with no redundancy or bloat.

    Completeness5/5

    The tool surface covers the full lifecycle: fetching market data, running dynamic backtests, retrieving results and artifacts, listing historical jobs, generating reports, and scanning live signals. There are no obvious missing operations for the domain; the set is comprehensive and self-contained.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

    Resources