OpenFinClaw CLI
Enables quant research, strategy generation, backtesting, and paper trading from natural language prompts, integrating with AI agents via an MCP server.
README
<div align="center">
<img src="imgs/logo.svg" alt="OpenFinClaw" width="680">
Your quant research team, in one prompt.
Research · strategy · backtest · paper trade — ship a complete quant workflow from a single natural-language prompt, inside Claude Code, Cursor, and 20+ AI agents.
🚀 Try it in 60 seconds — zero install
Run a full research → strategy → backtest loop in your browser. No install, no API key, real market data.
Quick Start · Example Prompts · Community · Platforms · vs. other tools
</div>
What you get
| 🧠 DeepAgent analysis skills | 60+ built-in — technical · fundamental · sentiment · risk · timing · factor |
| 🌍 Markets covered | 5 — US equities · A-shares · HK · Crypto · Forex |
| 🤖 Works with | 20+ AI platforms — Claude Code · Cursor · VS Code · Hermes · Windsurf · Codex … |
| 🔄 End-to-end flow | research → strategy → backtest → paper trade → publish to the leaderboard |
| ⚡ How you interact | streaming token-by-token in the terminal · MCP tool calls · in-browser playground |
<p align="center"> <img src="imgs/deepagent-backtest-metrics.png" alt="DeepAgent backtest result — Tesla Bollinger Bands" width="620"> <br/> <sub><em>Live output from <code>openfinclaw deepagent research</code> — one prompt: research → strategy → backtest → metrics.</em></sub> </p>
Example Prompts
Copy-paste any of these into openfinclaw deepagent research "…" (or drop them straight into your AI agent). Each one runs the full research → strategy → backtest loop.
📈 Technical analysis
Find RSI divergence signals on NVDA in the last 6 months, then backtest them.Compare a Bollinger Bands strategy on TSLA vs AAPL over 1 year — which wins?Screen the S&P 500 for golden-cross signals this month.
📊 Fundamentals & macro
Pull Apple's last 8 quarters of revenue, margins, and guidance. Summarize the trend.What's driving the NVDA move this quarter — earnings, guidance, or narrative?Compare AMD / INTC / NVDA on growth, margin, and valuation.
🎯 Strategy generation
Design a momentum strategy on US mega-cap tech. Backtest 2y. Tell me where it breaks.Write a mean-reversion strategy on BTC and show drawdown behavior through 2022.A-shares 沪深 300 日内轮动策略,年化目标 15%,最大回撤 < 10%。
🧪 Backtest & stress-test
Backtest a 50/200 SMA crossover on SPY from 2015. Include costs and slippage.Stress-test my forked strategy against the 2020 and 2022 crashes.
Want a ready-made one? Run
openfinclaw leaderboardto browse the community's highest-ranked strategies, thenforkany of them.
Quick Start
💡 Want to see it in action before installing? Try DeepAgent in your browser first.
60-second onboarding
npx @openfinclaw/cli@latest install # wizard + MCP configs + Skill registration + doctor
openfinclaw deepagent +research "盘点 BTC 周线" # streaming research / strategy / backtest
install runs the interactive wizard, writes MCP configs to every detected AI agent, persists your fch_ key to ~/.openfinclaw/config.json (chmod 600 on Unix), drops a SKILL.md under ~/.claude/skills/openfinclaw/ so Claude Code / Cursor auto-trigger on keywords like quant / backtest / 量化, and finishes with a connectivity check.
Non-interactive / CI:
npx @openfinclaw/cli@latest install --yes \
--platforms cursor,claude-code --tool-groups deepagent,strategy \
--api-key fch_xxx --register-skill
Just the wizard, no SKILL.md registration, no doctor: npx @openfinclaw/cli init.
CLI quick reference
A single fch_ key drives both DeepAgent and the strategy group. Resolution order: --api-key → OPENFINCLAW_API_KEY → ~/.openfinclaw/config.json.
| Group | Commands |
|---|---|
| DeepAgent | deepagent +research "<query>", deepagent health, deepagent skills, deepagent threads, deepagent messages, deepagent backtests, deepagent packages, deepagent download |
| Strategy | leaderboard, strategy-info, fork, list-strategies, validate, publish, publish-verify |
| Raw | api GET <path> · api POST <path> --json '<body>' — direct Hub Gateway call, auth pre-attached |
| System | install · init · skill-install · serve · doctor · update · examples |
+verb (e.g. deepagent +research) is the human-friendly streaming path; the bare verbs and MCP-only atomic triplet research_submit / research_poll / research_finalize are for agents/scripts. Run openfinclaw --help for the full surface.
Sample DeepAgent output — one prompt → strategy definition + backtest metrics + per-trade P&L + improvement notes:
<p align="center"> <img src="imgs/deepagent-backtest-metrics.png" alt="DeepAgent — strategy definition & performance metrics" width="49%" /> <img src="imgs/deepagent-backtest-trades.png" alt="DeepAgent — trades, conclusions & optimization suggestions" width="49%" /> </p>
Community: leaderboard → fork → publish
OpenFinClaw ships with a community strategy exchange. Browse what others are running, copy any strategy locally, tweak it, and publish back — think of it as a Hugging Face for quant strategies.
openfinclaw leaderboard --limit 20 # Browse top-ranked strategies
openfinclaw strategy-info <id> # See how a strategy performs
openfinclaw fork <id> # Copy to ./strategies/<slug>
# ... edit strategy.py, tweak fep.yaml ...
openfinclaw validate ./strategies/<slug> # Pre-flight FEP v2.0 check
openfinclaw publish ./my-strategy.zip # Ship to the leaderboard
openfinclaw publish-verify --submission-id <id> # Track backtest progress
Every published strategy is backtested server-side and ranked by live-market-equivalent returns — no self-reported numbers.
Supported Platforms
OpenFinClaw works with any MCP-compatible agent platform:
| Category | Platforms |
|---|---|
| Chat | Claude Desktop, Claude.ai, ChatGPT, Chatbox, LM Studio |
| IDEs | Claude Code, VS Code (Copilot), Cursor, Windsurf, JetBrains Junie, Zed, Cline, Continue.dev |
| CLI Agents | Codex (OpenAI), OpenCode, Amazon Q CLI |
| Frameworks | Hermes Agent, BeeAI, Swarms |
| AI Agents | OpenClaw, NanoClaw |
| Other | v0 (Vercel), Postman, Roo Code, Amp (Sourcegraph) |
Platform Config Examples
<details> <summary><b>Claude Code</b> — <code>~/.claude/settings.json</code></summary>
{
"mcpServers": {
"openfinclaw": {
"command": "npx",
"args": ["@openfinclaw/cli", "serve", "--tools=deepagent,strategy"],
"env": {
"OPENFINCLAW_API_KEY": "fch_xxx"
}
}
}
}
</details>
<details> <summary><b>Cursor</b> — <code>.cursor/mcp.json</code></summary>
{
"mcpServers": {
"openfinclaw": {
"command": "npx",
"args": ["@openfinclaw/cli", "serve", "--tools=deepagent,strategy"],
"env": {
"OPENFINCLAW_API_KEY": "fch_xxx"
}
}
}
}
</details>
For other platforms (VS Code, Hermes, Windsurf, Zed, OpenClaw, Junie, Trae, …), see configs/ for ready-to-copy templates. The shape is the same — only the host key (servers vs mcpServers vs context_servers) and config path differ.
Tool Groups & Context Optimization
Load only what you need to save tokens: serve --tools=deepagent (~1,400 tk) or serve --tools=strategy (~1,000 tk), or omit --tools for both.
| Group | Tools |
|---|---|
deepagent |
14 remote-agent tools — fin_deepagent_health / _skills / _research_submit / _research_poll / _research_finalize / _status / _cancel / _threads / _messages / _backtests / _backtest_result / _packages / _package_meta / _download_package |
strategy |
7 local FEP v2.0 tools — strategy_publish / strategy_validate / strategy_fork / strategy_leaderboard / strategy_get_info / strategy_list_local / strategy_publish_verify |
Environment Variables
Only one is required:
| Variable | Description |
|---|---|
OPENFINCLAW_API_KEY |
Unified fch_ key. Drives both strategy (Hub) and deepagent (Hub Gateway). Falls back to ~/.openfinclaw/config.json if unset. Get a key at hub.openfinclaw.ai. |
Advanced overrides (rarely needed): OPENFINCLAW_CONFIG_PATH, HUB_API_URL, DEEPAGENT_API_URL, REQUEST_TIMEOUT_MS, DEEPAGENT_SSE_TIMEOUT_MS — see packages/core/src/config.ts.
Development
git clone https://github.com/mirror29/openfinclaw-cli.git && cd openfinclaw-cli && pnpm install && pnpm build
OPENFINCLAW_API_KEY=<fch_...> node packages/cli/dist/index.js doctor # smoke test
Monorepo: @openfinclaw/core (zero-dep business logic) + @openfinclaw/cli (MCP server + terminal CLI + install wizard).
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.