Financial Modeling Prep (FMP) MCP Server
A Model Context Protocol (MCP) server that provides access to Financial Modeling Prep (FMP) API data through a standardized interface. This server allows AI assistants like Claude to access financial data programmatically.
Features
- Company Profiles: Access company information, descriptions, market caps, employee counts, and industry data
- Financial Statements: Retrieve income statements, balance sheets, and cash flow statements
- Financial Metrics: Get key metrics, ratios, and growth data
- Analyst Data: Access analyst estimates and recommendations
- SEC Filings: Find and retrieve SEC filing content
- Earnings Transcripts: Get earnings call transcripts
- Market Data: Access current stock prices and treasury yields
- Competitor Analysis: Find competitor companies
Installation
Prerequisites
- Python 3.8 or higher
- UV package manager (recommended) or pip
- Financial Modeling Prep API key
Setup
Clone this repository
Create a
.envfile in the project root with your API key:# Financial Modeling Prep API Configuration FMP_KEY=your_api_key_here # Optional: SEC API Configuration SEC_ACCESS=YourCompanyName YourEmail@example.comInstall dependencies using UV (recommended):
uv venv uv pip install -r requirements.txtOr using pip:
pip install -r requirements.txt
Running the Server
Using UV (Recommended)
UV provides faster dependency resolution and installation. To run the server with UV:
# Activate the virtual environment
uv venv activate
# Run the server
python fmp_mcp_server.py
The server will start and listen for connections on the default MCP port.
Using pip
# Create and activate a virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venvScriptsactivate
# Run the server
python fmp_mcp_server.py
Connecting with Claude Desktop
Claude Desktop can connect to MCP servers to access financial data. Here’s how to set it up:
- Download Claude Desktop
- Edit claude_desktop_config.json: “fmp_mcp_server”: { “command”: “uv”, “args”: [ “–directory”, “REPLACE ME WITH ABSOLUTE DIRECTORY TO REPO”, “run”, “fmp_mcp_server.py” ] }
Now Claude can use the FMP data through the MCP interface. You can ask Claude to:
- Get company profiles
- Retrieve financial statements
- Find SEC filings
- Access market data
- And more!
Example Queries for Claude
Once connected, you can ask Claude questions like:
- “I am considering a 3 year horizon investment, is Apple a good investment?”
- “Show me Tesla’s latest quarterly income statement”
- “Find the latest 10-K filing for Microsoft”
- “What are Amazon’s main competitors?”
- “Get the latest earnings transcript for Meta”
Configuration Options
The server supports the following environment variables:
FMP_KEY: Your Financial Modeling Prep API key (required)SEC_ACCESS: Your company name and email for SEC API access (optional)
Caching
The server implements a caching system to reduce API calls and improve performance:
- Financial data is cached by quarter/year
- Profile data is cached monthly
- Daily price data is cached for the current day
Cache files are stored in the DataCache directory.
Logging
Logs are written to the logs directory with rotation enabled:
- Maximum log file size: 10MB
- Number of backup files: 5
License
MIT License
Acknowledgements
- Financial Modeling Prep for providing the API
- MCP Server for the Model Context Protocol implementation
Financial Modeling Prep MCP Server
Project Details
- shadi-fsai/fmp_mcp_server
- MIT License
- Last Updated: 4/15/2025
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