mcp_query_table

mcp_query_table

A MCP server that queries financial website tables using Playwright, enabling automated data retrieval from sources like Tonghuashun and East Money, and exposing the results via MCP tools.

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README

mcp_query_table

mcp_query_table 是一个基于 playwright 的财经网页表格查询项目,支持把网页查询能力暴露为 MCP 服务。

当前统一项目目录要求如下:

/root/project/mcp_query_table

当前版本:

0.3.13

项目定位

  • 直接查询财经网站表格数据,减少手工复制和网页操作
  • 将查询能力封装为 Python 库,供脚本直接调用
  • 将查询能力封装为 MCP 服务,供 Cline、Cherry Studio、MCP Inspector 等客户端调用
  • 保留可选的 Streamlit 页面,便于把查询结果进一步交给大模型分析

当前支持

表格查询站点

  • 同花顺问财
  • 通达信问小达
  • 东方财富条件选股

对话提供商

  • 纳米搜索
  • 腾讯元宝
  • 百度 AI 搜索

项目结构

mcp_query_table/
├── mcp_query_table/
│   ├── __main__.py
│   ├── enums.py
│   ├── playwright_helper.py
│   ├── providers/
│   ├── server.py
│   ├── sites/
│   └── tool.py
├── docs/
│   ├── ARCHITECTURE.md
│   ├── DEVELOPMENT.md
│   ├── DEPLOYMENT.md
│   ├── API.md
│   ├── FAQ.md
│   └── OPERATIONS.md
├── examples/
├── streamlit/
├── requirements.txt
└── pyproject.toml

环境要求

  • Python 3.10+
  • 已安装 Chrome 或 Edge
  • 首次运行前已安装 Playwright 浏览器依赖

当前机器建议 Python 环境:

/root/.venv/bin/python

快速开始

安装依赖

cd /root/project/mcp_query_table
python3 -m pip install -r requirements.txt
python3 -m playwright install chromium

作为 Python 库使用

import asyncio

from mcp_query_table import AsyncBrowser, QueryType, Site, query


async def main():
    async with AsyncBrowser(
        endpoint="http://127.0.0.1:9222",
        executable_path="/usr/bin/google-chrome",
        user_data_dir="/root/.config/google-chrome",
    ) as browser:
        page = await browser.get_page()
        df = await query(
            page,
            query_input="收益最好的200只ETF",
            query_type=QueryType.ETF,
            max_page=1,
            site=Site.THS,
        )
        print(df.to_markdown())
        await browser.release_page(page)


asyncio.run(main())

启动 MCP 服务

标准输入输出模式:

cd /root/project/mcp_query_table
python3 -m mcp_query_table \
  --format markdown \
  --endpoint http://127.0.0.1:9222 \
  --executable_path /usr/bin/google-chrome \
  --user_data_dir /root/.config/google-chrome

SSE 模式:

cd /root/project/mcp_query_table
python3 -m mcp_query_table \
  --format markdown \
  --transport sse \
  --host 0.0.0.0 \
  --port 8000 \
  --endpoint http://127.0.0.1:9222 \
  --executable_path /usr/bin/google-chrome \
  --user_data_dir /root/.config/google-chrome

启动后:

  • SSE 地址:http://127.0.0.1:8000/sse
  • Streamable HTTP 地址:http://127.0.0.1:8000/mcp

常见使用场景

  • 查询“2024年涨幅最大的100只股票按市值排名”
  • 查询“年初至今收益率前50的基金”
  • 查询“今日涨幅前5的概念板块”
  • 将查询结果转成 Markdown 或 CSV 供大模型继续分析

运行注意事项

  • 浏览器窗口宽度要足够,避免站点切到移动版页面
  • 如果目标站点要求登录,建议提前在指定 user_data_dir 里完成登录
  • 无头模式下建议显式指定 user_data_dir
  • 各站点表结构不同,同一查询在不同站点得到的结果可能不同

文档

单文件版 i问财

仓库根目录下提供了 iwencai_single.py,用于在不启动 MCP 服务的情况下,直接查询新版 i问财 选股页并导出结果。

安装依赖:

pip install -r iwencai_single_requirements.txt
playwright install chromium

直接运行:

python iwencai_single.py

脚本默认会:

  1. 打开 i问财 选股结果页
  2. 自动切换到 100条/页
  3. 按分页抓取数据
  4. 导出到当前目录下的 行业概念_single.xlsx

如需复用,可直接调用:

from iwencai_single import QueryType, query_iwencai

参考

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