US Stock Data MCP Server
by mingyaw
This is a Model Context Protocol (MCP) server designed for accessing and updating US stock historical price data. It leverages local data storage and automatic updates from Yahoo Finance.
Last updated: N/A
What is US Stock Data MCP Server?
The US Stock Data MCP Server is a server application that provides access to historical US stock price data via the Model Context Protocol (MCP). It stores data locally in CSV format and can automatically update this data from Yahoo Finance.
How to use US Stock Data MCP Server?
- Install Python 3.x and clone the repository. 2. Install dependencies using
pip install -r requirements.txt. 3. Start the server usingpython server.py. 4. Access stock data using the provided MCP tools (get_local_stock_data,update_stock_data) or the resource URI (usstock://{symbol}/historical).
Key features of US Stock Data MCP Server
Local Data Storage
Automatic Updates from Yahoo Finance
Safe Data Writing
Flexible Time Range for Updates
Use cases of US Stock Data MCP Server
Backtesting trading strategies
Analyzing stock market trends
Building financial models
Integrating stock data into other applications
FAQ from US Stock Data MCP Server
Where is the data stored by default?
Where is the data stored by default?
The default data storage path is ~/Library/Application Support/us-market-data/data.
Can I customize the data storage path?
Can I customize the data storage path?
Yes, you can customize the data storage path using the US_STOCK_DATA_DIR environment variable.
How does the server handle duplicate data during updates?
How does the server handle duplicate data during updates?
Duplicate data is automatically handled during updates, keeping the latest records.
Is there a delay between update operations?
Is there a delay between update operations?
Yes, a 5-second delay is implemented between update operations to avoid frequent API requests.
What data fields are included in the stored stock data?
What data fields are included in the stored stock data?
The stored stock data includes the following fields: Date, Open, High, Low, Close, and Volume.