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AkTools Pro MCP Server

tchivs/mcp-aktools
4STDIOregistry active
Summary

This server wraps AkShare's financial data APIs into 65 MCP tools covering A-shares, Hong Kong and US stocks, cryptocurrencies, precious metals, forex, futures, and funds. You get historical prices with technical indicators (MACD, RSI, KDJ, BOLL), real-time anomaly scanning for surging stocks, institutional holdings, sector rotation analysis, and North-bound capital flows. The crypto side pulls from OKX and Binance for funding rates, open interest, and sentiment metrics. It includes a backtesting engine for SMA, RSI, and moving average crossover strategies, plus a virtual portfolio manager that tracks P&L across your simulated trades. Built-in prompts inject analyst workflows, and ASCII chart rendering lets you visualize trends directly in the chat interface. Dual-layer caching keeps responses fast.

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📈 AkTools Pro MCP Server

让 AI 成为你的金融分析师
Empower your AI Agents with Professional Financial Intelligence

Version PyPI License Python FastMCP GitHub stars

功能亮点 • 系统架构 • 快速开始 • 工具一览 • 实战示例


AkTools Pro 是一个基于 akshare 的增强型 MCP (Model Context Protocol) 服务器。它不仅仅是一个数据接口,更是一个内置了专业金融分析逻辑、交易策略和可视化能力的 AI 技能库。

无论是 A 股、港美股、加密货币还是贵金属,AkTools Pro 都能让你的 AI Agent 像资深分析师一样思考和回答。

🌟 核心特性

🧠 智能技能引擎💹 全球市场覆盖
内置 MCP Prompts 和 Resources,注入 "分析师" 人格与 SOP 标准流程。一站式覆盖 A股、港股、美股、加密货币、贵金属 等主流投资品种。
📊 可视化增强🛡️ 极致性能
支持在聊天界面直接绘制 ASCII 字符走势图,让数据趋势一目了然。采用 内存 + 磁盘 双层缓存机制,毫秒级响应,智能保护数据源。
💼 实战模拟🧪 策略实验室
内置虚拟持仓管理系统,支持 AI 自动跟踪 盈亏 (P&L) 与胜率统计。内置回测引擎,支持验证 SMA / RSI / MACD / BOLL / KDJ / MA_CROSS 等经典交易策略。

🏗 系统架构

graph TD
    User((User / AI Agent)) <-->|MCP Protocol| Server[AkTools Pro Server]
    
    subgraph "Core Engine"
        Server --> Skills[Skill Injector]
        Server --> Cache[Dual-Layer Cache]
        Server --> Visual[Visual Engine]
        Server --> Logic[Backtest/Analysis]
    end
    
    subgraph "Data Sources"
        Cache <--> AkShare[AkShare API]
        Cache <--> OKX[OKX / Binance]
        Cache <--> News[Financial News]
    end
    
    Skills -->|SOPs & Prompts| User
    Visual -->|ASCII Charts| User

🚀 快速开始

选择最适合你的安装方式,30秒内即可启动。

📦 方式 1: 自动安装 (推荐)

在你的 AI 终端中根据客户端类型执行:

OpenCode (Sisyphus)

opencode mcp add
# 1. Location: Global
# 2. Name: aktools-pro
# 3. Type: Local
# 4. Command: uvx aktools-pro

Claude Code / OpenAI Codex

claude mcp add aktools-pro -- uvx aktools-pro

Cursor / VS Code

在 mcpServers 配置文件中添加:

"aktools-pro": {
  "command": "uvx",
  "args": ["aktools-pro"]
}
🐳 方式 2: Docker 部署

适合服务器环境或偏好隔离的用户:

mkdir /opt/aktools-pro
cd /opt/aktools-pro
wget https://raw.githubusercontent.com/tchivs/aktools-pro/main/docker-compose.yml
docker-compose up -d
⚙️ 环境变量配置
变量名说明默认值
OKX_BASE_URLOKX 代理地址https://okx.com
BINANCE_BASE_URL币安代理地址https://www.binance.com
NEWSNOW_BASE_URL资讯接口地址https://newsnow.busiyi.world
TRANSPORTMCP 协议stdio

🛠 工具一览

AkTools Pro 提供了 65 个专业工具,分为以下核心模块:

📈 股票 & 市场 (Stock & Market)

覆盖 A股/港股/美股 的行情与基本面

  • 基础: search (搜代码), stock_info (个股信息)
  • 行情: market_prices (历史K线), stock_zt_pool_em (涨停池)
  • 数据: stock_indicators (财务指标), stock_lhb (龙虎榜), northbound_funds (北向资金)
  • 分析: sector_valuation (行业估值), sector_rotation (板块轮动), market_anomaly_scan (异动扫描)

₿ 加密货币 (Crypto)

接入 OKX/Binance 的深度数据

  • 行情: crypto_prices (K线), draw_crypto_chart (字符图)
  • 情绪: fear_greed_index (恐贪指数), crypto_sentiment_metrics (情绪指标)
  • 衍生品: okx_funding_rate (资金费率), okx_open_interest (持仓量)
  • 智能: binance_ai_report (AI研报), crypto_composite_diagnostic (综合诊断)

🥇 贵金属 (Precious Metals)

黄金/白银的期现货数据

  • 价格: pm_spot_prices (现货), pm_international_prices (外盘)
  • 库存: pm_etf_holdings (ETF持仓), pm_comex_inventory (COMEX库存)
  • 分析: pm_basis (期现基差), pm_composite_diagnostic (综合诊断)

💱 外汇 (Forex)

全球汇率行情与历史数据

  • 行情: fx_rates (即期汇率/交叉汇率)
  • 历史: fx_history (历史汇率)

🏗️ 期货 (Futures)

商品与金融期货深度数据

  • 行情: futures_prices (K线数据)
  • 库存: futures_inventory (交易所库存)
  • 基差: futures_basis (期现基差)
  • 持仓: futures_positions (仓单日报)

🏦 基金 (Funds)

公募基金与 ETF 数据

  • 基础: fund_info (基本信息), fund_ranking (基金排行)
  • 业绩: fund_nav (净值走势)
  • 持仓: fund_holdings (重仓股)
  • ETF: market_prices (asset=etf)

🌍 宏观经济 (Macro)

全球与中国宏观经济指标

  • 核心: macro_gdp (国内生产总值), macro_cpi (消费者物价指数)
  • 景气: macro_pmi (采购经理指数)
  • 金融: macro_interest_rate (基准利率), macro_money_supply (货币供应量)

🧠 智能技能 (AI Skills)

让 AI 具备专业分析师的思维

  • 股票 Prompts: analyze-stock (个股诊断), market-pulse (市场脉搏)
  • 加密 Prompts: analyze-crypto (币种分析), crypto-pulse (币圈脉搏)
  • 贵金属 Prompts: analyze-precious-metal (贵金属诊断), precious-metal-pulse (贵金属脉搏)
  • Resources: skill://trading/logic/technical-analysis, skill://trading/logic/precious-metals-analysis
  • Dynamic Resources: crypto://{symbol}/analysis, pm://{metal}/analysis, fund://{code}/analysis
  • Portfolio: portfolio_add (模拟交易), portfolio_view (盈亏分析), portfolio_chart (盈亏图表), trading_suggest (AI建议)
  • Cache: cache_status (缓存状态), cache_clear (清理缓存)

📋 完整工具列表

点击展开 65 个工具的完整列表

📈 股票 & 市场

工具名功能说明
search根据股票名称、公司名称等关键词查找股票代码
stock_info根据股票代码和市场获取股票基本信息
market_prices获取市场历史价格及技术指标 (MACD/RSI/KDJ/BOLL)
stock_news获取指定个股最近新闻动态
stock_news_global获取最新的全球财经快讯
stock_indicators_a获取A股财务报告关键指标
stock_indicators_hk获取港股财务报告关键指标
stock_indicators_us获取美股财务报告关键指标
institutional_holding_summary获取个股最新机构持仓与持股比例
stock_zt_pool_em获取A股所有涨停股票
stock_zt_pool_strong_em获取A股强势股池数据
stock_lhb_ggtj_sina获取A股龙虎榜个股上榜统计
stock_sector_fund_flow_rank获取A股行业资金流向数据
northbound_funds获取北向资金近10个交易日数据
sector_valuation获取申万一级行业估值(P/E、P/B)概览
sector_rotation基于行业资金流与涨跌幅识别短期强势行业
market_anomaly_scan扫描A股市场实时异动信号 (火箭发射、大笔买入等)
get_current_time获取当前时间及A股交易日信息

₿ 加密货币

工具名功能说明
crypto_prices获取OKX加密货币历史K线数据及技术指标
crypto_sentiment_metrics获取加密货币情绪指标
okx_funding_rate获取永续合约资金费率
okx_open_interest获取永续合约持仓量数据
binance_ai_report获取币安AI分析报告 (推荐)
fear_greed_index获取加密货币恐惧贪婪指数 (0-100)
crypto_composite_diagnostic一键获取加密货币综合诊断数据
draw_crypto_chart生成加密货币ASCII走势图
backtest_crypto_strategy加密货币策略回测 (SMA/RSI/MACD)

🥇 贵金属

工具名功能说明
pm_spot_prices获取上海金交所现货历史价格及技术指标
pm_international_prices获取国际贵金属实时价格 (伦敦金/COMEX)
pm_etf_holdings获取全球黄金/白银ETF持仓量变化
pm_comex_inventory获取COMEX交易所库存数据
pm_basis获取贵金属期现基差数据
pm_benchmark_price获取上海金银基准价格
pm_composite_diagnostic一键获取贵金属综合诊断数据

💱 外汇

工具名功能说明
fx_rates获取主要货币对实时汇率 (USD/EUR/JPY/GBP等)
fx_history获取指定货币对历史汇率数据

🏗️ 期货

工具名功能说明
futures_prices获取国内期货主力合约历史价格及技术指标
futures_inventory获取期货品种仓单库存数据
futures_basis获取期货与现货价格基差数据
futures_positions获取期货主力合约机构持仓排名

🏦 基金

工具名功能说明
fund_info获取基金基本信息 (名称/类型/规模/管理人)
fund_nav获取基金历史净值数据
fund_holdings获取基金股票持仓明细
fund_ranking获取基金排行榜 (按类型/收益率筛选)
market_prices获取ETF基金历史价格数据 (asset=etf)

🌍 宏观经济

工具名功能说明
macro_gdp获取中国GDP季度数据
macro_cpi获取中国CPI月度数据
macro_pmi获取中国PMI制造业指数
macro_interest_rate获取LPR贷款市场报价利率
macro_money_supply获取货币供应量(M0/M1/M2)数据

🧠 分析 & 回测

工具名功能说明
composite_stock_diagnostic一键获取个股技术面/基本面/消息面综合诊断
draw_ascii_chart生成股票ASCII走势图
backtest_strategy策略回测 (SMA/RSI/MACD/BOLL/MA_CROSS/KDJ)
trading_suggest基于AI分析给出投资建议

💼 模拟盘 & 系统

工具名功能说明
portfolio_add添加模拟持仓记录
portfolio_view查看模拟盘实时盈亏
portfolio_chart生成持仓盈亏ASCII柱状图
cache_status查看缓存状态
cache_clear清理指定或所有缓存

💡 实战示例

让 AI 帮你分析一只股票,体验 AkTools Pro 的强大:

User: 帮我分析一下 贵州茅台(600519) 的近期走势

Assistant: 好的,正在为您获取 贵州茅台(600519) 的综合数据...

[调用 market_prices, stock_indicators, stock_news...]

📊 **贵州茅台 (600519) 技术面分析**

Price
2100 +                                     |
     |              |                      |
2050 +            | | |                    |
     |          | | | |  |                 |
2000 +        | | | | |  | |               |
     |      | | | | | |  | | |             |
1950 +    | | | | | | |  | | |             +------- 现价: 1985.00
     |  | | | | | | | |  | | |             |
1900 +| | | | | | | | |  | | |             |
     +-------------------------------------+
      10-01   10-15   11-01   11-15   12-01

📈 **诊断结论**:
1. **趋势**: 短期均线(MA5/10)呈多头排列,RSI(14) 为 62.5,处于强势区间。
2. **资金**: 北向资金近3日连续净买入,机构持仓保持稳定。
3. **估值**: 当前 PE(TTM) 为 28.5,处于历史 40% 分位,具备安全边际。

💡 **操作建议**: 持有 (Score: 85)

🆚 版本对比

功能特性AkTools (原版)AkTools Pro (本版)
项目架构单文件脚本📦 模块化工程
回测引擎❌✅ 支持
模拟持仓❌✅ 支持
ASCII 图表❌✅ 支持
SOP 技能库❌✅ 支持
类型安全❌✅ 全类型提示

👨‍💻 开发与贡献

# 同步环境
uv sync

# 运行检查
uv run aktools-pro inspect

# 运行测试
uv run pytest tests/ -v

# 代码检查
uv run ruff check mcp_aktools

Built with ❤️ for the Quantitative Trading Community

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Registryactive
Packageaktools-pro
TransportSTDIO
UpdatedJan 29, 2026
View on GitHub