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fmp_mcp_server_finance

MCP.Pizza Chef: shadi-fsai

The Financial Modeling Prep (FMP) MCP Server is a Model Context Protocol server that exposes extensive financial data through a standardized interface. It enables AI assistants like Claude to programmatically access company profiles, financial statements, key metrics, analyst data, SEC filings, earnings transcripts, market data, and competitor analysis. This server simplifies integration of real-time financial information into AI workflows, supporting informed decision-making and financial analysis.

Use This MCP server To

Retrieve detailed company profiles for financial analysis Access income statements, balance sheets, and cash flow data Fetch key financial metrics and growth ratios Obtain analyst estimates and stock recommendations Retrieve SEC filings and regulatory documents Access earnings call transcripts for sentiment analysis Get real-time stock prices and treasury yields Perform competitor company comparisons

README

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

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

fmp_mcp_server_finance FAQ

How do I authenticate the FMP MCP Server?
You need a Financial Modeling Prep API key to authenticate and access data.
What programming languages can I use with this MCP server?
The server is implemented in Python 3.8+, but you can interact with it via any MCP-compatible client.
Can this server provide real-time stock market data?
Yes, it provides current stock prices and treasury yields through the FMP API.
Is it possible to access SEC filings through this server?
Yes, the server exposes SEC filing content for companies covered by FMP.
How does this server handle financial statement data?
It provides structured access to income statements, balance sheets, and cash flow statements.
Can I get analyst recommendations using this server?
Yes, analyst estimates and recommendations are available via the server.
What AI assistants are compatible with this MCP server?
It works with any MCP-compatible AI assistant, including Claude, GPT-4, and Gemini.
What are the prerequisites for installing this server?
Python 3.8+, UV or pip package manager, and a valid FMP API key are required.