Skip to main content
Glama

Financial Modeling Prep MCP Server

by shadi-fsai

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

Related MCP server: Ledger CLI MCP Server

Installation

Prerequisites

  • Python 3.8 or higher

  • UV package manager (recommended) or pip

  • Financial Modeling Prep API key

Setup

  1. Clone this repository

  2. Create a .env file 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.com
  3. Install dependencies using UV (recommended):

    uv venv uv pip install -r requirements.txt

    Or 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: venv\Scripts\activate # 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:

  1. Download Claude Desktop

  2. 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

-
security - not tested
-
license - not tested
-
quality - not tested

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/shadi-fsai/fmp_mcp_server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server