Futu MCP

WEB_API_BASE_URL=http://localhost:8001 MCP_PORT=9001 python mcp_service/main.py

- .env会读取EXTERNAL_MCP_ENDPOINT（默认http://localhost:9001/mcp）。若你修改 MCP 端口或部署方式，请同步更新该变量，以便 Web 服务在/mcp/status或重定向时提供正确地址。
- 访问http://localhost:8001/mcp时会收到 307 重定向到外部 MCP，方便老配置顺滑迁移；建议尽快在 MCP 客户端里把地址改成新的端口。

# 单个股票查询 curl -X POST http://localhost:8001/api/quote/stock_quote \ -H "Content-Type: application/json" \ -d '{"code_list": ["HK.00700"]}' # 批量股票查询（推荐） curl -X POST http://localhost:8001/api/quote/stock_quote \ -H "Content-Type: application/json" \ -d '{ "code_list": ["HK.00700", "HK.09660", "HK.00005"], "optimization": {"only_essential_fields": true} }'

{ "ret_code": 0, "ret_msg": "获取股票报价成功", "data": { "quotes": [{ "code": "HK.00700", "last_price": 325.4, "change_val": 2.8, "change_rate": 0.87, "volume": 12345678, "turnover": 4.01e9 }] } }

# 获取日K线数据 curl -X POST http://localhost:8001/api/quote/history_kline \ -H "Content-Type: application/json" \ -d '{ "code": "HK.00700", "ktype": "K_DAY", "start": "2024-01-01", "end": "2024-12-31", "max_count": 100 }' # 获取分钟级K线数据 curl -X POST http://localhost:8001/api/quote/history_kline \ -H "Content-Type: application/json" \ -d '{ "code": "HK.00700", "ktype": "K_30M", "max_count": 48 }'

- K_1M,K_3M,K_5M,K_15M,K_30M,K_60M(分钟线)
- K_DAY(日线),K_WEEK(周线),K_MON(月线)

# 计算单个指标 curl -X POST http://localhost:8001/api/analysis/technical_indicators \ -H "Content-Type: application/json" \ -d '{ "code": "HK.00700", "indicators": ["rsi"], "ktype": "K_DAY", "period": 30 }' # 计算多个指标 curl -X POST http://localhost:8001/api/analysis/technical_indicators \ -H "Content-Type: application/json" \ -d '{ "code": "HK.00700", "indicators": ["macd", "rsi", "bollinger_bands"], "ktype": "K_DAY" }' # 计算所有指标（完整分析） curl -X POST http://localhost:8001/api/analysis/technical_indicators \ -H "Content-Type: application/json" \ -d '{ "code": "HK.00700", "indicators": ["all"], "ktype": "K_DAY" }'

curl -X POST http://localhost:8001/api/analysis/snapshot \ -H "Content-Type: application/json" \ -d '{ "code": "HK.00700", "include_history": true, "include_technicals": true, "technical_period": 120 }' | jq '.'

- 一次请求即可拿到行情、技术面、资金面、最新策略、基本面信号、持仓概览
- insights字段自动给出多维统计（如利好/利空数量、策略条数、最新价格）
- 可通过参数裁剪历史K线、资金流、技术指标等模块
- MCP 工具get_analysis_snapshot直接复用该接口，免去多接口串联

# 查看缓存状态 curl http://localhost:8001/api/cache/status # 预加载热门股票数据 curl -X POST http://localhost:8001/api/cache/preload \ -H "Content-Type: application/json" \ -d '{ "symbols": ["HK.00700", "HK.09660", "HK.00005"], "days": 30, "ktypes": ["K_DAY", "K_30M"] }' # 清理缓存 curl -X DELETE http://localhost:8001/api/cache/clear \ -H "Content-Type: application/json" \ -d '{"cache_type": "memory"}'

# 保存一条策略建议 curl -X POST http://localhost:8001/api/recommendations \ -H "Content-Type: application/json" \ -d '{ "code": "HK.00700", "action": "BUY", "rationale": "突破年线并放量，RSI回升至50上方", "confidence": 0.72, "timeframe": "swing", "tags": ["技术面", "突破"], "source": "kimi-k2-thinking-turbo", "evidence": [ {"type": "indicator", "name": "MACD", "value": "金叉"}, {"type": "news", "title": "Q3 财报高于预期"} ] }' # 查询策略建议（可按代码、标签、采纳状态等过滤） curl -X POST http://localhost:8001/api/recommendations/query \ -H "Content-Type: application/json" \ -d '{ "code": "HK.00700", "tag": "技术面", "limit": 20 }'

接口会自动在data/recommendations.db中持久化记录，既能通过 HTTP 使用，也会在 MCP 客户端中以save_recommendation/get_recommendations工具呈现，方便大模型写入与查询策略建议。

当你希望把某只股票的行情、资讯、策略和个人持仓集中展示给同事或终端用户，可以通过新的create_dashboard_session接口为任意标的生成一个可共享的 Web 看板：

# 1) 生成会话，得到 Web URL curl -X POST http://localhost:8001/api/dashboard/session \ -H "Content-Type: application/json" \ -d '{"code": "HK.00700"}' # 响应示例： # { # "session_id": "1Np4dJ6xG6M", # "url": "http://localhost:8001/web/dashboard?session=1Np4dJ6xG6M" # } # 2) 把 url 发给浏览器或 MCP 客户端，页面会自动： # • 订阅 Futu 报价/盘口/逐笔/分时等推送，并实时刷新图表 # • 拉取 Metaso 搜索结果，按“利好/利空”分区展示 # • 展示资金流向 / 资金分布 / 历史K线等关键指标 # • 读取最近的策略建议和（若可用）个人持仓摘要 # • 会话 ID 会落盘到 data/dashboard_sessions.json，重启服务后仍可复用链接 # ⚙️ 如需让 MCP 返回公网地址，可设置 DASHBOARD_BASE_URL 环境变量： # export DASHBOARD_BASE_URL="https://your-domain.com" # 这样 create_dashboard_session 工具会直接返回公网可访问的 URL。 看板页面顶部会展示所有已订阅的股票，并实时显示 Futu 订阅额度使用情况，可一键取消订阅，便于控制配额。 > 另外，服务启动后控制台会输出 http://localhost:8001/web，打开即可查看所有看板的列表总览，并快速进入详情页。

MCP 侧同样会暴露create_dashboard_session工具，LLM 只需给出股票代码即可获得实时大屏的链接，实现“问即得 URL”的工作流。

# 确认Python版本 python --version # 需要 3.10+ # 创建虚拟环境（推荐） python -m venv venv source venv/bin/activate # Linux/Mac # 或 venv\Scripts\activate # Windows # 安装依赖 pip install -r requirements_enhanced.txt

# 1. 下载富途OpenD客户端 # https://www.futunn.com/download/openAPI # 2. 启动OpenD # - 登录富途账号 # - 确保有相应市场的行情权限 # - 默认端口: 11111 # 3. 验证连接 telnet 127.0.0.1 11111

# macOS安装 brew install redis brew services start redis # Ubuntu安装 sudo apt-get install redis-server sudo systemctl start redis # 验证Redis redis-cli ping # 应返回 PONG

# macOS安装 brew install ta-lib pip install TA-Lib # Ubuntu安装 sudo apt-get install libta-lib-dev pip install TA-Lib # 注意: 如果安装失败，系统会自动使用纯Python实现

# 🌟 启动智能助手 - 一站式解决所有需求 python futu_assistant.py # 智能助手提供： # 🎯 菜单式操作界面 # 🧠 智能建议和自动响应 # 🔧 故障自动诊断 # 📊 实时状态监控 # 🚀 一键重启和修复 # 💡 使用指导和帮助

import httpx import asyncio class FutuAnalysisAPI: def __init__(self, base_url="http://localhost:8001"): self.base_url = base_url self.client = httpx.AsyncClient() async def get_stock_quote(self, codes: list): """获取股票报价""" response = await self.client.post( f"{self.base_url}/api/quote/stock_quote", json={"code_list": codes} ) return response.json() async def get_technical_analysis(self, code: str, indicators: list = ["all"]): """获取技术分析""" response = await self.client.post( f"{self.base_url}/api/analysis/technical_indicators", json={ "code": code, "indicators": indicators, "ktype": "K_DAY" } ) return response.json() # 使用示例 api = FutuAnalysisAPI() quote = await api.get_stock_quote(["HK.00700"]) analysis = await api.get_technical_analysis("HK.00700")

{ "mcpServers": { "futu-enhanced": { "url": "http://127.0.0.1:8001/mcp", "name": "富途量化分析平台" } } }

# 1. 检查OpenD是否运行 netstat -an | grep 11111 # 2. 检查账号登录状态 # 确保OpenD客户端已登录并有行情权限 # 3. 重启服务 python main_enhanced.py

# Redis可选，不影响核心功能 # 如需启用Redis: brew install redis && brew services start redis # macOS # 或 sudo apt-get install redis-server && sudo systemctl start redis # Ubuntu

# 清理缓存，重新获取数据 curl -X DELETE http://localhost:8001/api/cache/clear \ -H "Content-Type: application/json" \ -d '{"cache_type": "sqlite"}' # 预加载数据 curl -X POST http://localhost:8001/api/cache/preload \ -H "Content-Type: application/json" \ -d '{"symbols": ["HK.00700"], "days": 60}'

ERROR: Received request before initialization was complete

# 使用稳定的HTTP API替代MCP curl -X POST http://localhost:8001/api/quote/stock_quote \ -H "Content-Type: application/json" \ -d '{"code_list": ["HK.00700"]}'

# 1. 服务状态检查 curl http://localhost:8001/health # 2. 缓存状态检查 curl http://localhost:8001/api/cache/status # 3. 测试核心功能 curl -X POST http://localhost:8001/api/quote/stock_quote \ -H "Content-Type: application/json" \ -d '{"code_list": ["HK.00700"]}' # 4. 性能测试 time curl -X POST http://localhost:8001/api/analysis/technical_indicators \ -H "Content-Type: application/json" \ -d '{"code": "HK.00700", "indicators": ["rsi"]}'

FROM python:3.10-slim WORKDIR /app COPY requirements_enhanced.txt . RUN pip install -r requirements_enhanced.txt COPY . . EXPOSE 8001 CMD ["uvicorn", "main_enhanced:app", "--host", "0.0.0.0", "--port", "8001"]

# 构建并运行 docker build -t futu-mcp-enhanced . docker run -d -p 8001:8001 \ -v $(pwd)/data:/app/data \ --name futu-mcp \ futu-mcp-enhanced

# /etc/systemd/system/futu-mcp.service [Unit] Description=富途MCP增强服务 After=network.target [Service] Type=simple User=ubuntu WorkingDirectory=/opt/mcp_futu Environment=PATH=/opt/mcp_futu/venv/bin ExecStart=/opt/mcp_futu/venv/bin/python main_enhanced.py Restart=always RestartSec=3 [Install] WantedBy=multi-user.target

# 启用服务 sudo systemctl enable futu-mcp sudo systemctl start futu-mcp sudo systemctl status futu-mcp