Skip to main content

MCP协议的A股量化分析工具,为AI Agent提供股票推荐、行情分析、K线图绘制等功能

Project description

MCP-A股量化分析服务

基于MCP协议的A股量化分析工具,为AI Agent提供股票推荐、行情分析、K线图绘制等功能

功能特性

  • 📈 A股精选股票推荐
  • 📊 K线图绘制(支持MA5/MA10等技术指标)
  • 🔍 股票历史数据查询
  • 📉 技术指标计算(MACD, BOLL等)
  • 🧮 量化分析模型

快速开始

环境要求

  • Python 3.12+
  • 安装依赖库:
uv add "mcp[cli]" matplotlib 
uv add "mcp[cli]" pandas
uv add "mcp[cli]" tushare

运行服务

mcp dev server.py

MCP配置

"ashare_quant": {
    "command": "uv",
    "args": [
        "--directory",
        "path/mcp-servers/python/mcp-ashare-quant",
        "run", 
        "server.py"
    ],
    "disabled": false,
    "autoApprove": []
}

API说明

股票推荐

  • recommend_a_shares(): 推荐符合条件的A股股票
    • 参数: limit(数量), min_price(最低价), max_price(最高价)等
    • 返回: 股票列表及推荐理由

K线图绘制

  • plot_kline(): 绘制股票K线图
    • 参数: data(股票数据), indicators(技术指标)
    • 返回: 图表文件路径

数据获取

  • get_stock_data(): 获取股票历史数据
    • 参数: code(股票代码), count(数据条数)
    • 返回: OHLCV数据

技术指标

  • calculate_technical_indicators(): 计算技术指标
    • 参数: data(股票数据), indicators(指标列表)
    • 返回: 包含指标值的数据

使用示例

获取股票推荐

recommendations = recommend_a_shares(limit=15)

绘制K线图

data = get_stock_data(code="sh600519", count=20)
plot_kline(data, indicators=["MA5","MA10"])

注意事项

  • 使用前需配置Tushare API token
  • 图表功能需要matplotlib支持
  • 数据获取有频率限制,请合理使用

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mcp_ashare_quant-0.1.4.tar.gz (12.8 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mcp_ashare_quant-0.1.4-py3-none-any.whl (27.0 kB view details)

Uploaded Python 3

File details

Details for the file mcp_ashare_quant-0.1.4.tar.gz.

File metadata

  • Download URL: mcp_ashare_quant-0.1.4.tar.gz
  • Upload date:
  • Size: 12.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.16

File hashes

Hashes for mcp_ashare_quant-0.1.4.tar.gz
Algorithm Hash digest
SHA256 5ef0d9d46b2a1b390917430f3b51c64b9248f6f547385d96cfcf60575a2b07f6
MD5 ea7df65177c43cc542b4875ee971bb7e
BLAKE2b-256 1110585f48727fa91bcbd90ad40e95c57f240e93dec88d3b749937dff5e51971

See more details on using hashes here.

File details

Details for the file mcp_ashare_quant-0.1.4-py3-none-any.whl.

File metadata

File hashes

Hashes for mcp_ashare_quant-0.1.4-py3-none-any.whl
Algorithm Hash digest
SHA256 33f610162e8ba2383788d340d247ede11fb25880557aadc6661bb160e9a49cfc
MD5 89df5a0d5d454b128097a305d15ad181
BLAKE2b-256 c509f7d05cc50b86ed5d8efdb8899255eb09eed482b0f0e564303d23646e5f2e

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page