blave-agent MCP Server
Blave-TW/blave-agent
[](https://agentrank-ai.com/tool/Blave-TW--blave-agent/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) Quant infrastructure for AI agents — a free, open-source desktop workspace for macOS and Windows where your Claude Code or Codex turns a trading idea into a backtested strategy and runs it live.
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
Blave-TW/blave-agent is a Python tool licensed under Apache-2.0. Quant infrastructure for AI agents — a free, open-source desktop workspace for macOS and Windows where your Claude Code or Codex turns a trading idea into a backtested strategy and runs it live. Topics: ai-agent, algorithmic-trading, backtesting, claude-code, codex, crypto, electron, macos, mcp, quant, taiwan-stock, trading-bot, windows.
Ranked #5291 out of 24846 indexed tools.
Ecosystem
Score Breakdown
102 stars → growing community
Last commit 29d ago → recently updated
No issues filed → no history to score
1 contributor → solo project
No dependents → no downstream usage
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
How to Improve
Matched Queries
From the README
# Blave Agent ## Quant Workspace for AI Agents Build, backtest and trade strategies live with Claude Code or Codex. Free and open source. **English** | [繁體中文](README.zh-TW.md) | [简体中文](README.zh-CN.md) | [日本語](README.ja.md) | [Español](README.es.md) | [Português](README.pt.md) | [Tiếng Việt](README.vi.md) https://github.com/user-attachments/assets/7b33edb7-9c65-4e19-854a-40295c6e8b74 [Download for macOS](https://github.com/Blave-TW/blave-agent/releases/latest) · [Download for Windows](https://download.blave.org/desktop/win/Blave-Setup.exe) · [Quick start (from source)](#quick-start) · [Run it with your computer off](https://blave.org/agent/en) Star the repo if this is useful — and Watch › Releases to get notified of new versions. ## What Makes It Different ### Backtests That Check for Overfitting and Use Real Fees Overfitting: parameters that just happen to fit past data. - Every Type A backtest runs a Monte Carlo permutation test by default (MCPT, `lib/validation.py`) andRead full README on GitHub →
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