Financial Modeling Prep MCP Server

MIT License
5

Integrations

  • Provides access to Apple's financial data, including company profile, financial statements, metrics, and analyst estimates for investment analysis

  • Allows access to Meta's earnings transcripts, financial statements, company profile, and market performance metrics

  • Enables retrieval of Tesla's financial statements, company profile, and market performance data for financial analysis

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

  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

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
A
license - permissive license
-
quality - not tested

local-only server

The server can only run on the client's local machine because it depends on local resources.

A Model Context Protocol server that enables AI assistants like Claude to programmatically access financial data from Financial Modeling Prep API, including company profiles, financial statements, metrics, SEC filings, and market data.

  1. Features
    1. Installation
      1. Prerequisites
      2. Setup
    2. Running the Server
      1. Using UV (Recommended)
      2. Using pip
    3. Connecting with Claude Desktop
      1. Example Queries for Claude
        1. Configuration Options
          1. Caching
            1. Logging
              1. License
                1. Acknowledgements

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