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MCP Yahoo Finance

by maxscheijen

MCP Yahoo Finance

PyPI - Version PyPI - Python Version PyPI - License

A Model Context Protocol (MCP) server for Yahoo Finance interaction. This server provides tools to get pricing, company information and more.

Please note that mcp-yahoo-finance is currently in early development. The functionality and available tools are subject to change and expansion as I continue to develop and improve the server.

Installation

You don't need to manually install mcp-yahoo-finance if you use uv. We'll use uvx to directly run mcp-yahoo-finance.

I would recommend using this method if you simply want to use the MCP server.

Using pip

Using pip.

pip install mcp-yahoo-finance

Using Git

You can also install the package after cloning the repository to your machine.

git clone git@github.com:maxscheijen/mcp-yahoo-finance.git cd mcp-yahoo-finance uv sync

Configuration

Claude Desktop

Add this to your claude_desktop_config.json:

{ "mcpServers": { "yahoo-finance": { "command": "uvx", "args": ["mcp-yahoo-finance"] } } }

You can also use docker:

{ "mcpServers": { "yahoo-finance": { "command": "docker", "args": ["run", "-i", "--rm", "IMAGE"] } } }

VSCode

Add this to your .vscode/mcp.json:

{ "servers": { "yahoo-finance": { "command": "uvx", "args": ["mcp-yahoo-finance"] } } }

Examples of Questions

  1. "What is the stock price of Apple?"
  2. "What is the difference in stock price between Apple and Google?"
  3. "How much did the stock price of Apple change between 2024-01-01 and 2025-01-01?"

Build

Docker:

docker build -t [IMAGE] .

Test with MCP Inspector

npx @modelcontextprotocol/inspector uv run mcp-yahoo-finance

You must be authenticated.

A
security – no known vulnerabilities
A
license - permissive license
A
quality - confirmed to work

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

A Model Context Protocol server that enables interaction with Yahoo Finance to retrieve stock pricing, company information, and historical financial data through natural language queries.

  1. Installation
    1. Using pip
    2. Using Git
  2. Configuration
    1. Claude Desktop
    2. VSCode
  3. Examples of Questions
    1. Build
      1. Test with MCP Inspector

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