Futu Stock MCP Server

Futu Stock MCP Server

mcp server for futuniuniu stock

shuizhengqi1

Research & Data
Visit Server

README

Futu Stock MCP Server

Python Version License OpenAPI

基于模型上下文协议(MCP)的富途证券行情交易接口服务器。将富途OpenAPI功能以标准化的MCP协议提供给AI模型使用,支持行情订阅、数据查询等功能。

🌟 特性

  • 🔌 完全兼容 MCP 2.0 协议标准
  • 📊 支持港股、美股、A股等市场的实时行情
  • 🔄 支持实时数据订阅和推送
  • 📈 支持K线、逐笔、买卖盘等多维度数据
  • 🔒 安全的API调用和数据访问机制
  • 🛠 提供完整的开发工具和示例代码

⚠️ 前置要求

在使用本项目之前,您需要:

  1. 拥有富途证券账户并开通OpenAPI权限
  2. 安装并运行富途的OpenD网关程序(官方文档
  3. 根据您的需求订阅相应的行情权限

🔒 安全提示

  • 请勿在代码中硬编码任何账号密码信息
  • 确保.env文件已添加到.gitignore
  • 妥善保管您的API访问凭证
  • 遵守富途OpenAPI的使用条款和限制

📝 免责声明

本项目是一个开源工具,旨在简化富途OpenAPI的接入流程。使用本项目时请注意:

  1. 遵守相关法律法规和富途OpenAPI的使用条款
  2. 自行承担使用本项目进行交易的风险
  3. 本项目不提供任何投资建议
  4. 使用本项目前请确保您已获得所需的行情权限

Features

  • Standard MCP 2.0 protocol compliance
  • Comprehensive Futu API coverage
  • Real-time data subscription support
  • Market data access
  • Derivatives information
  • Account query capabilities
  • Resource-based data access
  • Interactive prompts for analysis

Prerequisites

  • Python 3.10+
  • Futu OpenAPI SDK
  • Model Context Protocol SDK
  • uv (recommended)

Installation

  1. Clone the repository:
git clone https://github.com/yourusername/futu-stock-mcp-server.git
cd futu-stock-mcp-server
  1. Install uv:
# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows (PowerShell)
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"
  1. Create and activate a virtual environment:
# Create virtual environment
uv venv

# Activate virtual environment
# On macOS/Linux:
source .venv/bin/activate
# On Windows:
.venv\Scripts\activate
  1. Install dependencies:
# Install in editable mode
uv pip install -e .
  1. Copy the environment file and configure:
cp .env.example .env

Edit the .env file with your server settings:

HOST=0.0.0.0
PORT=8000
FUTU_HOST=127.0.0.1
FUTU_PORT=11111

Development

Managing Dependencies

Add new dependencies to pyproject.toml:

[project]
dependencies = [
    # ... existing dependencies ...
    "new-package>=1.0.0",
]

Then update your environment:

uv pip install -e .

Code Style

This project uses Ruff for code linting and formatting. The configuration is in pyproject.toml:

[tool.ruff]
line-length = 100
target-version = "py38"

[tool.ruff.lint]
select = ["E", "F", "I", "N", "W", "B", "UP"]

Run linting:

uv pip install ruff
ruff check .

Run formatting:

ruff format .

Usage

  1. Start the server:
python -m futu_stock_mcp_server.server
  1. Connect to the server using an MCP client:
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client

async def main():
    server_params = StdioServerParameters(
        command="python",
        args=["src/server.py"]
    )
    
    async with stdio_client(server_params) as (read, write):
        async with ClientSession(read, write) as session:
            # Initialize the connection
            await session.initialize()
            
            # List available tools
            tools = await session.list_tools()
            
            # Call a tool
            result = await session.call_tool(
                "get_stock_quote",
                arguments={"symbols": ["HK.00700"]}
            )
            
            # Access a resource
            content, mime_type = await session.read_resource(
                "market://HK.00700"
            )
            
            # Get a prompt
            prompt = await session.get_prompt(
                "market_analysis",
                arguments={"symbol": "HK.00700"}
            )

if __name__ == "__main__":
    import asyncio
    asyncio.run(main())

Available API Methods

Market Data Tools

  • get_stock_quote: Get stock quote data
  • get_market_snapshot: Get market snapshot
  • get_cur_kline: Get current K-line data
  • get_history_kline: Get historical K-line data
  • get_rt_data: Get real-time data
  • get_ticker: Get ticker data
  • get_order_book: Get order book data
  • get_broker_queue: Get broker queue data

Subscription Tools

  • subscribe: Subscribe to real-time data
  • unsubscribe: Unsubscribe from real-time data

Derivatives Tools

  • get_option_chain: Get option chain data
  • get_option_expiration_date: Get option expiration dates
  • get_option_condor: Get option condor strategy data
  • get_option_butterfly: Get option butterfly strategy data

Account Query Tools

  • get_account_list: Get account list
  • get_asset_info: Get asset information
  • get_asset_allocation: Get asset allocation information

Market Information Tools

  • get_market_state: Get market state
  • get_security_info: Get security information
  • get_security_list: Get security list

Stock Filter Commands

get_stock_filter

Filter stocks based on various conditions.

Parameters:

  • base_filters (optional): List of basic stock filters
    {
        "field_name": int,  # StockField enum value
        "filter_min": float,  # Optional minimum value
        "filter_max": float,  # Optional maximum value
        "is_no_filter": bool,  # Optional, whether to skip filtering
        "sort_dir": int  # Optional, sort direction
    }
    
  • accumulate_filters (optional): List of accumulate filters
    {
        "field_name": int,  # AccumulateField enum value
        "filter_min": float,
        "filter_max": float,
        "is_no_filter": bool,
        "sort_dir": int,
        "days": int  # Required, number of days to accumulate
    }
    
  • financial_filters (optional): List of financial filters
    {
        "field_name": int,  # FinancialField enum value
        "filter_min": float,
        "filter_max": float,
        "is_no_filter": bool,
        "sort_dir": int,
        "quarter": int  # Required, financial quarter
    }
    
  • market (optional): Market code (e.g. "HK.Motherboard", "US.NASDAQ")
  • page (optional): Page number, starting from 1 (default: 1)
  • page_size (optional): Number of results per page, max 200 (default: 200)

Supported Market Codes:

  • HK.Motherboard: Hong Kong Main Board
  • HK.GEM: Hong Kong GEM
  • HK.BK1911: H-Share Main Board
  • HK.BK1912: H-Share GEM
  • US.NYSE: NYSE
  • US.AMEX: AMEX
  • US.NASDAQ: NASDAQ
  • SH.3000000: Shanghai Main Board
  • SZ.3000001: Shenzhen Main Board
  • SZ.3000004: Shenzhen ChiNext

Example:

# Get stocks with price between 10 and 50 HKD in Hong Kong Main Board
filters = {
    "base_filters": [{
        "field_name": 5,  # Current price
        "filter_min": 10.0,
        "filter_max": 50.0
    }],
    "market": "HK.Motherboard"
}
result = await client.get_stock_filter(**filters)

Notes:

  • Limited to 10 requests per 30 seconds
  • Each page returns maximum 200 results
  • Recommended to use no more than 250 filter conditions
  • Maximum 10 accumulate conditions of the same type
  • Dynamic data sorting (like current price) may change between pages
  • Cannot compare different types of indicators (e.g. MA5 vs EMA10)

Resources

Market Data

  • market://{symbol}: Get market data for a symbol
  • kline://{symbol}/{ktype}: Get K-line data for a symbol

Prompts

Analysis

  • market_analysis: Create a market analysis prompt
  • option_strategy: Create an option strategy analysis prompt

Error Handling

The server follows the MCP 2.0 error response format:

{
    "jsonrpc": "2.0",
    "id": "request_id",
    "error": {
        "code": -32000,
        "message": "Error message",
        "data": null
    }
}

Security

  • The server uses secure WebSocket connections
  • All API calls are authenticated through the Futu OpenAPI
  • Environment variables are used for sensitive configuration

Development

Adding New Tools

To add a new tool, use the @mcp.tool() decorator:

@mcp.tool()
async def new_tool(param1: str, param2: int) -> Dict[str, Any]:
    """Tool description"""
    # Implementation
    return result

Adding New Resources

To add a new resource, use the @mcp.resource() decorator:

@mcp.resource("resource://{param1}/{param2}")
async def new_resource(param1: str, param2: str) -> Dict[str, Any]:
    """Resource description"""
    # Implementation
    return result

Adding New Prompts

To add a new prompt, use the @mcp.prompt() decorator:

@mcp.prompt()
async def new_prompt(param1: str) -> str:
    """Prompt description"""
    return f"Prompt template with {param1}"

License

MIT License

Available MCP Functions

Market Data Functions

get_stock_quote

Get stock quote data for given symbols.

symbols = ["HK.00700", "US.AAPL", "SH.600519"]
result = await session.call_tool("get_stock_quote", {"symbols": symbols})

Returns quote data including price, volume, turnover, etc.

get_market_snapshot

Get market snapshot for given symbols.

symbols = ["HK.00700", "US.AAPL", "SH.600519"]
result = await session.call_tool("get_market_snapshot", {"symbols": symbols})

Returns comprehensive market data including price, volume, bid/ask prices, etc.

get_cur_kline

Get current K-line data.

result = await session.call_tool("get_cur_kline", {
    "symbol": "HK.00700",
    "ktype": "K_1M",  # K_1M, K_5M, K_15M, K_30M, K_60M, K_DAY, K_WEEK, K_MON
    "count": 100
})

get_history_kline

Get historical K-line data.

result = await session.call_tool("get_history_kline", {
    "symbol": "HK.00700",
    "ktype": "K_DAY",
    "start": "2024-01-01",
    "end": "2024-03-31"
})

get_rt_data

Get real-time trading data.

result = await session.call_tool("get_rt_data", {"symbol": "HK.00700"})

get_ticker

Get ticker data (detailed trades).

result = await session.call_tool("get_ticker", {"symbol": "HK.00700"})

get_order_book

Get order book data.

result = await session.call_tool("get_order_book", {"symbol": "HK.00700"})

get_broker_queue

Get broker queue data.

result = await session.call_tool("get_broker_queue", {"symbol": "HK.00700"})

Subscription Functions

subscribe

Subscribe to real-time data.

result = await session.call_tool("subscribe", {
    "symbols": ["HK.00700", "US.AAPL"],
    "sub_types": ["QUOTE", "TICKER", "K_1M"]
})

Subscription types:

  • "QUOTE": Basic quote
  • "ORDER_BOOK": Order book
  • "TICKER": Trades
  • "RT_DATA": Real-time data
  • "BROKER": Broker queue
  • "K_1M" to "K_MON": K-line data

unsubscribe

Unsubscribe from real-time data.

result = await session.call_tool("unsubscribe", {
    "symbols": ["HK.00700", "US.AAPL"],
    "sub_types": ["QUOTE", "TICKER"]
})

Options Functions

get_option_chain

Get option chain data.

result = await session.call_tool("get_option_chain", {
    "symbol": "HK.00700",
    "start": "2024-04-01",
    "end": "2024-06-30"
})

get_option_expiration_date

Get option expiration dates.

result = await session.call_tool("get_option_expiration_date", {
    "symbol": "HK.00700"
})

get_option_condor

Get option condor strategy data.

result = await session.call_tool("get_option_condor", {
    "symbol": "HK.00700",
    "expiry": "2024-06-30",
    "strike_price": 350.0
})

get_option_butterfly

Get option butterfly strategy data.

result = await session.call_tool("get_option_butterfly", {
    "symbol": "HK.00700",
    "expiry": "2024-06-30",
    "strike_price": 350.0
})

Account Functions

get_account_list

Get account list.

result = await session.call_tool("get_account_list", {"random_string": "dummy"})

get_funds

Get account funds information.

result = await session.call_tool("get_funds", {"random_string": "dummy"})

get_positions

Get account positions.

result = await session.call_tool("get_positions", {"random_string": "dummy"})

get_max_power

Get maximum trading power.

result = await session.call_tool("get_max_power", {"random_string": "dummy"})

get_margin_ratio

Get margin ratio for a security.

result = await session.call_tool("get_margin_ratio", {"symbol": "HK.00700"})

Market Information Functions

get_market_state

Get market state.

result = await session.call_tool("get_market_state", {"market": "HK"})

Available markets: "HK", "US", "SH", "SZ"

get_security_info

Get security information.

result = await session.call_tool("get_security_info", {
    "market": "HK",
    "code": "00700"
})

get_security_list

Get security list for a market.

result = await session.call_tool("get_security_list", {"market": "HK"})

get_stock_filter

Get filtered stock list based on conditions.

result = await session.call_tool("get_stock_filter", {
    "market": "HK.Motherboard",
    "base_filters": [{
        "field_name": 1,  # Price
        "filter_min": 10.0,
        "filter_max": 50.0,
        "sort_dir": 1  # Ascending
    }],
    "page": 1,
    "page_size": 50
})

Time Function

get_current_time

Get current server time.

result = await session.call_tool("get_current_time", {"random_string": "dummy"})

Returns timestamp, formatted datetime, date, time and timezone.

Recommended Servers

Crypto Price & Market Analysis MCP Server

Crypto Price & Market Analysis MCP Server

A Model Context Protocol (MCP) server that provides comprehensive cryptocurrency analysis using the CoinCap API. This server offers real-time price data, market analysis, and historical trends through an easy-to-use interface.

Featured
TypeScript
MCP PubMed Search

MCP PubMed Search

Server to search PubMed (PubMed is a free, online database that allows users to search for biomedical and life sciences literature). I have created on a day MCP came out but was on vacation, I saw someone post similar server in your DB, but figured to post mine.

Featured
Python
dbt Semantic Layer MCP Server

dbt Semantic Layer MCP Server

A server that enables querying the dbt Semantic Layer through natural language conversations with Claude Desktop and other AI assistants, allowing users to discover metrics, create queries, analyze data, and visualize results.

Featured
TypeScript
mixpanel

mixpanel

Connect to your Mixpanel data. Query events, retention, and funnel data from Mixpanel analytics.

Featured
TypeScript
Sequential Thinking MCP Server

Sequential Thinking MCP Server

This server facilitates structured problem-solving by breaking down complex issues into sequential steps, supporting revisions, and enabling multiple solution paths through full MCP integration.

Featured
Python
Nefino MCP Server

Nefino MCP Server

Provides large language models with access to news and information about renewable energy projects in Germany, allowing filtering by location, topic (solar, wind, hydrogen), and date range.

Official
Python
Vectorize

Vectorize

Vectorize MCP server for advanced retrieval, Private Deep Research, Anything-to-Markdown file extraction and text chunking.

Official
JavaScript
Mathematica Documentation MCP server

Mathematica Documentation MCP server

A server that provides access to Mathematica documentation through FastMCP, enabling users to retrieve function documentation and list package symbols from Wolfram Mathematica.

Local
Python
kb-mcp-server

kb-mcp-server

An MCP server aimed to be portable, local, easy and convenient to support semantic/graph based retrieval of txtai "all in one" embeddings database. Any txtai embeddings db in tar.gz form can be loaded

Local
Python
Research MCP Server

Research MCP Server

The server functions as an MCP server to interact with Notion for retrieving and creating survey data, integrating with the Claude Desktop Client for conducting and reviewing surveys.

Local
Python