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FactorHub MCP Server

FactorHub MCP Server

by michaelfeng

FactorHub MCP Server

English | 中文


中文

A 股量化数据 MCP 服务器 —— 让 Claude、Cursor 等 AI 工具直接查询因子数据、行情、估值、回测。

功能列表

工具

说明

set_api_key

设置你的 API Key(可选,不设置使用免费体验额度)

list_factors

因子列表(分类、搜索)

get_factor_scores

因子评分指标(年化收益、夏普、IC等)

get_factor_nav

因子净值曲线

get_market_daily

个股日线行情(OHLCV)

get_index_daily

指数日线(上证、沪深300等)

get_valuation

估值指标(PE、PB、PS、股息率)

get_stock_info

个股基本信息

get_stock_list

股票筛选

get_trade_dates

交易日历

run_backtest

量化策略回测

快速开始

方式一:免费体验(无需注册)

使用托管服务器,无需 API Key,自带免费额度(10 次/天)。

Claude Desktop —— 编辑 claude_desktop_config.json:

{
  "mcpServers": {
    "factorhub": {
      "command": "npx",
      "args": ["-y", "@smithery/cli@latest", "run", "factorhub"]
    }
  }
}

或直接远程连接:

https://factorhub.cn/mcp/sse

方式二:安装到本地(使用自己的 API Key)

注册 factorhub.cn,在 API Key 管理页 生成 Key,获得更高额度。

pip install factorhub-mcp

Claude Desktop —— 编辑 claude_desktop_config.json:

{
  "mcpServers": {
    "factorhub": {
      "command": "factorhub-mcp",
      "env": {
        "FACTORHUB_API_KEY": "fh_你的密钥"
      }
    }
  }
}

Cursor —— 编辑 .cursor/mcp.json,格式同上。

Claude Code —— 运行:

claude mcp add factorhub -- env FACTORHUB_API_KEY=fh_你的密钥 factorhub-mcp

OpenClaw —— 添加到技能配置:

providers:
  factorhub:
    type: mcp
    command: factorhub-mcp
    env:
      FACTORHUB_API_KEY: "fh_你的密钥"

方式三:通过 Smithery 安装

在 Smithery 一键安装,自动配置到你的 AI 客户端。

使用示例

配置完成后,直接对你的 AI 助手说:

  • "查看 FactorHub 有哪些因子"

  • "获取动量因子的历史表现"

  • "帮我查一下贵州茅台最近一年的行情"

  • "用低估值策略回测沪深300成分股"

  • "对比动量因子和价值因子的夏普比率"

也可以在对话中设置自己的 Key 来获得更多额度:

  • "用我的 API Key fh_xxx 登录 FactorHub"

定价

方案

API 调用/天

回测/天

价格

Free

20

3

¥0

Pro

10,000

20

¥99/月

Pro Max

40,000

100

¥199/月

Ultra

不限

不限

¥899/月

升级方案:factorhub.cn/pricing

架构

本 MCP 服务器是一个轻量客户端,通过 HTTPS 调用 FactorHub 公开 API,不直接访问数据库,不包含任何私有逻辑。

AI 助手  →  MCP 协议  →  factorhub-mcp  →  HTTPS  →  factorhub.cn/api/v1

安全

  • API Key 存储在环境变量中,不会硬编码

  • 所有通信使用 HTTPS 加密

  • 本地不存储任何用户数据

  • 服务端强制频率限制


Related MCP server: AI-Kline MCP Server

English

China A-share market data for AI agents. Query factor scores, market quotes, valuations, and run strategy backtests — all through the Model Context Protocol (MCP).

Features

Tool

Description

set_api_key

Set your API key (optional, defaults to free trial quota)

list_factors

List factors with category/search filters

get_factor_scores

Factor metrics: annual return, Sharpe, max drawdown, IC, etc.

get_factor_nav

Factor NAV curve for trend analysis

get_market_daily

Stock daily OHLCV data

get_index_daily

Index daily data (SSE, CSI 300, CSI 500, etc.)

get_valuation

Valuation metrics: PE, PB, PS, dividend yield

get_stock_info

Stock basic info

get_stock_list

Stock screening by exchange/industry

get_trade_dates

Trading calendar

run_backtest

Strategy backtesting

Quick Start

Option 1: Try Free (No Registration)

Use the hosted server directly — no API key needed, includes free trial quota (10 calls/day).

Claude Desktop — add to claude_desktop_config.json:

{
  "mcpServers": {
    "factorhub": {
      "command": "npx",
      "args": ["-y", "@smithery/cli@latest", "run", "factorhub"]
    }
  }
}

Or connect directly via SSE:

https://factorhub.cn/mcp/sse

Option 2: Install with Your API Key

For higher quotas, register at factorhub.cn and get your API key at the API Keys page.

pip install factorhub-mcp

Claude Desktop — add to claude_desktop_config.json:

{
  "mcpServers": {
    "factorhub": {
      "command": "factorhub-mcp",
      "env": {
        "FACTORHUB_API_KEY": "fh_your_api_key_here"
      }
    }
  }
}

Cursor — add to .cursor/mcp.json (same format as above).

Claude Code — run:

claude mcp add factorhub -- env FACTORHUB_API_KEY=fh_your_api_key_here factorhub-mcp

OpenClaw — add to your skill config:

providers:
  factorhub:
    type: mcp
    command: factorhub-mcp
    env:
      FACTORHUB_API_KEY: "fh_your_api_key_here"

Option 3: Smithery

Install via Smithery for automatic setup with any MCP client.

Usage Examples

Once configured, ask your AI assistant:

  • "List all available factors on FactorHub"

  • "Show momentum factor performance"

  • "Get Kweichow Moutai stock data for the past year"

  • "Backtest a low-valuation strategy on CSI 300"

  • "Compare Sharpe ratios of momentum vs value factors"

Set your own API key mid-conversation for higher quotas:

  • "Set my FactorHub API key to fh_xxx"

Pricing

Plan

API Calls/Day

Backtest/Day

Price

Free

20

3

¥0

Pro

10,000

20

¥99/mo

Pro Max

40,000

100

¥199/mo

Ultra

Unlimited

Unlimited

¥899/mo

Upgrade at factorhub.cn/pricing.

Architecture

This MCP server is a thin client that calls the FactorHub public API. It does not access any database directly or contain proprietary logic.

AI Agent  →  MCP Protocol  →  factorhub-mcp  →  HTTPS  →  factorhub.cn/api/v1

Security

  • API key is stored in environment variables, never hardcoded

  • All communication uses HTTPS

  • No user data is stored locally

  • Rate limiting is enforced server-side

License

MIT

Available Tools

11 tools
get_factor_navC

获取因子净值曲线数据,用于分析因子历史表现趋势。

Inputs: code (required), start_date, end_date. Returns: result

get_factor_scoresB

获取单个因子的详细评分指标:年化收益、夏普比率、最大回撤、波动率、Alpha、Beta、IC均值等。

Inputs: code (required), start_date, end_date. Returns: result

get_index_dailyC

获取指数日线行情。常用:000001.SH(上证)、399001.SZ(深证)、000300.SH(沪深300)、000905.SH(中证500)。

Inputs: ts_code, start_date, end_date. Returns: result

get_market_dailyB

获取个股日线行情数据(OHLCV + 涨跌幅)。ts_code 如 000001.SZ、600519.SH。

Inputs: ts_code (required), start_date, end_date. Returns: result

get_stock_infoB

获取单只股票基本信息:名称、行业、上市日期、市场板块等。

Inputs: ts_code (required). Returns: result

get_stock_listC

按条件筛选股票列表。可按交易所(SSE/SZSE)、行业筛选。

Inputs: exchange, industry, page, page_size. Returns: result

get_trade_datesB

获取交易日历,查询指定时间段内的交易日列表。

Inputs: start_date, end_date. Returns: result

get_valuationC

获取股票估值指标:PE、PB、PS、股息率、总市值、流通市值、换手率等。

Inputs: ts_code, trade_date. Returns: result

list_factorsA

获取因子列表。支持按分类和关键词搜索。返回因子代码、名称、分类、年化收益、夏普比率等。

Inputs: category, search, page, page_size. Returns: result

run_backtestB

执行量化策略回测。内置策略:limit_up_first_board(涨停首板)、low_valuation(低估值)、momentum(动量)、mean_reversion(均值回归)。返回年化收益、夏普比率、最大回撤等。

Inputs: strategy_type, strategy_params, universe, start, +2 more. Returns: result

set_api_keyA

Inputs: api_key (required). Returns: result

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

    TDQS

    B3.4/5.0

    Scored across 11 tools

    Disambiguation5/5

    Each tool targets a distinct aspect of financial data analysis: factor performance vs scores, index vs stock data, stock info vs list, valuation, backtesting, and configuration. No two tools serve the same purpose.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (e.g., get_factor_nav, list_factors, run_backtest). The conventions are uniform across all 11 tools.

    Tool Count5/5

    With 11 tools, the server covers core operations for factor analysis, stock data, index data, backtesting, and configuration. The count is well-scoped without being overwhelming or insufficient.

    Completeness4/5

    The tool set covers essential CRUD-like operations for factor data, stocks, indices, and backtesting. Minor gaps exist, such as lack of bulk data retrieval or more customizable backtest parameters, but the core workflows are well-supported.

    Maintenance

    ActivityNo data
    ResponsivenessSyncing

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