Finance MCP Server
Enables fetching financial statements (Income Statement, Balance Sheet, Cash Flow) for public companies using data from Yahoo Finance, free and no API key required.
README
Finance MCP Server
A Model Context Protocol (MCP) server that provides financial data for LLMs. This server specifically fetches financial statements (Income Statement, Balance Sheet, Cash Flow) for public companies.
Features
- Free to use: No API keys required.
- Structured Data: Returns data in consistent Pydantic models (JSON schema).
- Easy Integration: Works with any MCP-compliant client (Claude Desktop, Cursor, etc.).
Data Source
This package retrieves financial data from Yahoo Finance using the yfinance library.
Note: This tool is for educational and research purposes. Please respect Yahoo Finance's terms of service.
Installation & Usage
Option 1: Quick Use with uvx (Recommended)
You can run this server directly without standard installation using uv (or uvx).
Add this to your MCP settings configuration (e.g., ~/.config/Claude/claude_desktop_config.json or your IDE's MCP config):
{
"mcpServers": {
"finance": {
"command": "uvx",
"args": [
"finance-mcp-free"
]
}
}
}
Option 2: Local Development (Git Clone)
If you want to modify the code or run it locally:
-
Clone the repository:
git clone https://github.com/ryar001/finance_mcp.git cd finance_mcp -
Install dependencies:
# Using uv (recommended) uv venv source .venv/bin/activate uv sync # Or using pip pip install -e . -
Run the server:
# Run directly finance-mcp # Or via fastmcp dev for auto-reload fastmcp dev finance_mcp/main_mcp.py:mcp_server
Data Models
The server returns data structured according to strict Pydantic models to ensure reliability for your LLM.
Example Return Format
All financial statements return a dictionary where keys are dates and values are the statement object.
Income Statement Example:
{
"30/09/2023": {
"ticker": "AAPL",
"period": "30/09/2023",
"total_revenue": 89498000000,
"net_income": 22956000000,
"cost_of_revenue": 49071000000,
"gross_profit": 40427000000,
"operating_expenses": 13458000000,
"operating_income": 26969000000,
...
}
}
The data is strictly typed to ensure your LLM can reliably query fields like total_revenue, net_income, etc.
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