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Stock Research Data Foundation MCP Server

by godermai
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Python
Local

Stock Research Data Foundation

本地优先的个人股票研究数据底座，基于 DuckDB + Parquet + SQLite + MCP

快速开始

1. 环境准备

# 克隆项目
cd /path/to/get-stock-data

# 创建虚拟环境
python3 -m venv .venv
source .venv/bin/activate  # macOS/Linux

# 安装依赖
pip install -e ".[dev]"

2. 配置

# 复制环境变量模板
cp .env.example .env

# 编辑 .env，填入你的 Tushare Pro token
# 获取地址: https://tushare.pro/register
echo 'TUSHARE_TOKEN=your_token_here' >> .env

3. 初始化数据库

python scripts/init_db.py

4. 运行测试

python -m pytest tests/ -v

5. 启动数据同步

from src.jobs import run_sync_security_master, run_sync_market_daily

# 同步证券主数据
result = run_sync_security_master(tushare_token="your_token")
print(result)

# 同步某日行情
result = run_sync_market_daily(trade_date="20240628")
print(result)

6. 启动 MCP 服务

python -m mcp.local_stock_server

Related MCP server: TapeDeck

架构概览

┌─────────────────────────────────────────────────┐
│              Skills (7个研究Skill)                │
├─────────────────────────────────────────────────┤
│           MCP Server (11个工具, stdio)            │
├─────────────────────────────────────────────────┤
│        Silver Layer (DuckDB + Parquet)           │
├─────────────────────────────────────────────────┤
│        Bronze Layer (原始数据落地)                 │
├─────────────────────────────────────────────────┤
│     Adapters (Tushare/AKShare/BaoStock/CNINFO)  │
└─────────────────────────────────────────────────┘

数据源

数据源

角色

需要 Token

说明

Tushare Pro

主数据源

是

结构化API，字段文档齐全

AKShare

广度采集

否

多源公开数据，易变化

BaoStock

验证源

否

免费，volume单位为股

CNINFO

公告权威源

否

官方公告+PDF下载

规范化规则

  • 符号格式: 600519.SH / 000001.SZ / 920001.BJ / 00700.HK

  • 成交量单位: 股 (Tushare/AKShare的手×100，BaoStock已是股)

  • 成交额单位: 元 (Tushare的千元×1000)

  • 财务数据: 保留累计值和单季衍生值，标注来源

目录结构

get-stock-data/
├── src/
│   ├── adapters/          # 4个数据源适配器
│   ├── normalize/         # 符号/单位/字段/单季 归一化
│   ├── lake/              # Bronze/Silver/DuckDB视图
│   ├── models/            # Schema定义 + DQ规则
│   ├── jobs/              # 4个同步任务
│   ├── config.py          # 统一配置
│   ├── exceptions.py      # 自定义异常
│   └── logging_config.py  # 日志配置
├── mcp/                   # 本地MCP服务 (11个工具)
├── skills/                # 7个研究Skill
├── tests/                 # 62+ 测试
├── audits/                # Phase 1审计文件
├── scripts/init_db.py     # 数据库初始化
├── check_progress.py      # 进度检查 (crontab每2小时)
└── agents/                # 多智能体治理文件

MCP 工具列表

工具

功能

最大返回行数

search_security

搜索证券

20 (可分页)

get_market_history

获取行情历史

500/symbol

get_latest_quote

获取最新报价

50 symbols

get_financial_statements

获取财务报表

1000

get_financial_metrics

获取财务指标

50

get_announcements

获取公告

50 (可分页)

search_announcements

搜索公告

20 (可分页)

compare_sources

多源对比

200

get_data_freshness

数据新鲜度

20

run_data_quality_check

运行DQ检查

N/A

export_dataset

导出数据集

100000

多智能体治理

角色

执行者

职责

项目经理

Claude Code

进度监控/风险/验收

需求管理专家

Claude Code

需求矩阵/覆盖度/缺口

实施工程师

Cascade

编码/修复/测试

License

MIT

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