FMP

Provides financial data from Financial Modeling Prep through an MCP server for AI-assisted investment research.

python

0

GitHub Stars

python

Language

4 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "digibugcat-fmp-mcp": {
      "command": "uv",
      "args": [
        "run",
        "fastmcp",
        "run",
        "server.py"
      ],
      "env": {
        "FMP_API_KEY": "your_api_key_here"
      }
    }
  }
}

You set up this MCP server to provide financial data from Financial Modeling Prep for AI-assisted investment research. Built with FastMCP 2.0 and Python, it orchestrates multiple data endpoints into workflow and atomic tools, enabling you to fetch company profiles, market context, earnings insights, valuations, and more with minimal setup.

How to use

To use the server, start it with your MCP client and connect to the local or remote endpoint as configured. You can then invoke workflow tools to get comprehensive research outputs, or drill into atomic tools for detailed data like company overviews, financial statements, earnings information, and news. The architecture supports parallel data retrieval, graceful degradation, and in-memory caching to speed up repeated requests.

How to install

Prerequisites you need before installing this MCP server:

Python 3.11 or newer is required
Install the MCP runtime and utility CLI you will use to run the server
Set up access to Financial Modeling Prep data

Run the server

uv sync
uv run fastmcp run server.py

Claude Desktop / Claude Code configuration

If you are using Claude, configure the MCP connection as shown to run the server via the MCP runner.

{
  "mcpServers": {
    "fmp_mcp": {
      "command": "uv",
      "args": ["run", "fastmcp", "run", "server.py"],
      "env": {
        "FMP_API_KEY": "your_api_key_here"
      }
    }
  }
}

Available tools

stock_brief

Quick snapshot tool returning profile, price action, valuation, analyst consensus, insider signals, and headlines.

market_context

Produces full market context including rates, yield curve, sector rotation, breadth, movers, and economic calendar.

earnings_setup

Pre-earnings positioning with consensus estimates, beat/miss history, analyst momentum, price drift, and insider signals.

fair_value_estimate

Multi-method valuation including DCF, earnings-based, peer multiples, analyst targets, and a blended estimate.

earnings_postmortem

Post-earnings synthesis covering beat/miss, trend comparison, analyst reaction, market response, and guidance tone.

company_overview

Company profile, quote, key metrics, and analyst ratings.

financial_statements

Income statement, balance sheet, and cash flow (annual/quarterly).

analyst_consensus

Analyst grades, price targets, and forward estimates.

earnings_info

Historical and upcoming earnings with beat/miss tracking.

price_history

Historical daily prices with technical context.

stock_search

Search for stocks by name or ticker.

insider_activity

Insider trading activity and transaction statistics.

institutional_ownership

Top institutional holders and position changes.

stock_news

treasury_rates

Current Treasury yields and yield curve.

economic_calendar

Upcoming economic events and releases.

market_overview

Sector performance, gainers, losers, most active.

earnings_transcript

Earnings call transcripts with pagination.

revenue_segments

Revenue breakdown by product and geography.

peer_comparison

Peer group valuation and performance comparison.

dividends_info

Dividend history, yield, growth, and payout analysis.

earnings_calendar

Upcoming earnings dates with optional symbol filter.

etf_lookup

ETF holdings or stock ETF exposure (dual-mode with auto-detect).

estimate_revisions

Analyst sentiment momentum: forward estimates, grade changes, beat rate.

fmp_coverage_gaps

Docs parity introspection: endpoint families not yet implemented in this MCP server.