What is Fmp Mcp Server Finance

fmp_mcp_server_finance is a Model Context Protocol (MCP) server that provides programmatic access to financial data from the Financial Modeling Prep (FMP) API through a standardized interface. It enables AI assistants to retrieve and utilize financial information effectively.

Use cases

Use cases include developing financial applications, conducting market research, performing competitor analysis, generating financial reports, and providing insights for investment decisions.

How to use

To use fmp_mcp_server_finance, clone the repository, set up your environment by creating a .env file with your FMP API key, install the necessary dependencies using UV or pip, and run the server. The server will listen for connections on the default MCP port.

Key features

Key features include access to company profiles, financial statements (income statements, balance sheets, cash flow statements), financial metrics, analyst data, SEC filings, earnings transcripts, market data, and competitor analysis.

Where to use

fmp_mcp_server_finance can be used in various fields such as finance, investment analysis, business intelligence, and any application requiring access to comprehensive financial data.

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 [email protected]
   

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

• Financial Modeling Prep for providing the API
• MCP Server for the Model Context Protocol implementation