A-share

Provides access to A股 stock data including basics, historical quotes, financials, and macro data via an MCP server.
  • python

19

GitHub Stars

python

Language

5 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs
{
  "mcpServers": {
    "firmmaple-a-share-mcp-server": {
      "command": "python",
      "args": [
        "mcp_server.py"
      ]
    }
  }
}

You run an MCP server focused on the A股 market to answer questions about stocks, historical data, financials, macroeconomics, and more. It exposes a consistent querying interface that you can connect to from AI assistants or other MCP clients to fetch up‑to‑date stock information and analytical data.

How to use

You connect your MCP client to the local or remote MCP server and request data using the available tools. The server provides stock basic information, historical K data, financial statements, macroeconomic data, market overviews, and technical indicators. You can ask questions at different levels, such as details for a single stock, comparisons across groups, or time-bound analyses, and your AI assistant will format the responses for easy interpretation.

How to install

Prerequisites you need before installation: Python 3.10 or higher and the pip package manager. You also should be prepared to install optional dependencies for advanced capabilities.

# Clone the project repository
git clone https://github.com/firmmaple/a-share-mcp-server.git
cd a-share-mcp-server

# Install core dependencies
pip install -r requirements.txt

# Optional: install advanced technical indicators library
pip install pandas-ta

Run the server

Start the MCP server locally with Python. The server will listen on the default port and accept MCP connections from your client.

python mcp_server.py

Configure your MCP client

In your AI assistant or MCP client, register the local server as an MCP endpoint so you can send queries and receive structured responses.

{
  "mcpServers": {
    "a_share_mcp": {
      "command": "python",
      "args": ["mcp_server.py"],
      "cwd": "."
    }
  }
}

Available tools

get_stock_basic_info

Query basic stock information such as code, name, listed status, and industry for a given stock code.

get_historical_k_data

Fetch historical K-line data for a stock over a specified date range.

get_profit_data

Retrieve profit-related metrics for a company, such as net income and margins, by year or quarter.

get_operation_data

Obtain operating metrics from financial statements to assess ongoing business performance.

get_growth_data

Access growth indicators like revenue growth and earnings growth over time.

get_balance_data

Get balance sheet data including assets, liabilities, and equity for a given period.

get_cash_flow_data

Retrieve cash flow statements to evaluate cash generation and usage.

get_dupont_data

Compute Dupont analysis metrics to understand return on equity drivers.

get_trade_dates

Fetch valid trading dates within a specified range or calendar context.

get_all_stock

List all available stocks covered by the data source.

get_stock_industry

Retrieve industry classifications for stocks and sector groupings.

get_sz50_stocks

Get the list of SZ50 constituent stocks.

get_hs300_stocks

Get the list of HS300 constituent stocks.

get_zz500_stocks

Get the list of ZZ500 constituent stocks.

get_deposit_rate_data

Obtain recent or historical deposit rates from macro data sources.

get_loan_rate_data

Access loan rate data for macroeconomic context.

get_required_reserve_ratio_data

Query reserve requirement data to understand monetary policy indicators.

get_money_supply_data_month

Fetch monthly money supply metrics.

get_money_supply_data_year

Fetch yearly money supply metrics.

get_shibor_data

Retrieve SHIBOR rate data for interbank liquidity outlook.

get_technical_indicators

Compute or retrieve technical indicators such as moving averages, MACD, RSI.

get_moving_averages

Calculate or access moving averages for trend analysis.

calculate_bollinger_bands

Compute Bollinger Bands for volatility and price channel assessment.

calculate_macd

Calculate MACD indicator for momentum signaling.

calculate_rsi

Calculate RSI for relative strength and momentum.

get_valuation_metrics

Retrieve valuation metrics to assess relative pricing.

calculate_peg_ratio

Compute PEG ratio as a growth-adjusted valuation multiple.

calculate_ddm_valuation

Perform Dividend Discount Model based valuation.

calculate_dcf_valuation

Perform Discounted Cash Flow valuation analysis.

get_comparable_analysis

Run a comparable company analysis to benchmark valuations.

get_market_analysis_timeframe

Analyze market data across a defined timeframe.

format_trading_calendar

Format and interpret trading calendar data for planning.

validate_stock_code

Validate stock code formats and correctness.

get_latest_trading_date

Fetch the latest trading date in the dataset.

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