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cloudQuant/backtrader-mcp

by Various

Local-first MCP server for AI-assisted Backtrader strategy development: immutable datasets, private drafts, and bounded subprocess backtests via 30 typed tools. Offline & backtest-

MCP

cloudQuant/backtrader-mcp

Added 21 Sept 2026

#ai-agents #algorithmic-trading #backtesting #claude-code #codex #llm #mcp #mcp-server

Overview

Local-first MCP server that lets AI assistants develop Backtrader strategies. Provides 30 typed tools for managing immutable datasets, private drafts, and running bounded subprocess backtests. Works offline and is backtest-only.

Best for

Best for
AI-assisted Backtrader strategy developers who want offline, sandboxed backtesting

Use cases

  • Develop and iterate on Backtrader strategies with an AI assistant
  • Run backtests in a sandboxed subprocess without network access
  • Manage versioned datasets and private strategy drafts locally

How to use

Tested with

Claude Desktop, Claude Code, ChatGPT

Notes

Local-first MCP server that lets AI assistants develop Backtrader strategies. Provides 30 typed tools for managing immutable datasets, private drafts, and running bounded subprocess backtests. Works offline and is backtest-only.

1 stars on GitHub. Last updated 2026-09-20. Licensed MIT.

Use cases

  • Develop and iterate on Backtrader strategies with an AI assistant
  • Run backtests in a sandboxed subprocess without network access
  • Manage versioned datasets and private strategy drafts locally

Pros

  • Local-first design keeps data private and offline
  • Bounded subprocess backtests prevent runaway execution
  • Typed tools give AI assistants a clear interface

Cons

  • Only 1 star, early stage
  • Backtest-only, no live trading support
  • Requires Python environment and MCP client setup

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Local-first design keeps data private and offline
  • Bounded subprocess backtests prevent runaway execution
  • Typed tools give AI assistants a clear interface

Cons

  • Only 1 star, early stage
  • Backtest-only, no live trading support
  • Requires Python environment and MCP client setup

Pairs with

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