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MCP server for Financial Modeling Prep - 19 tools for market data via Claude

Project description

fmp-mcp

Financial intelligence for your AI agent — powered by live market data.

Give Claude (or any MCP-compatible AI) the ability to analyze stocks, screen markets, compare peers, read earnings calls, and track sector rotations — all grounded in real financial data from Financial Modeling Prep.

This isn't a raw API wrapper. Each tool is purpose-built for a specific analytical task, composing multiple data sources into structured, analysis-ready outputs designed for AI consumption.

What your AI can do

Market Intelligence

  • get_market_context — One-call market snapshot: indices, sectors, gainers/losers, economic events
  • get_sector_overview — Sector and industry performance with P/E valuations
  • get_news — Stock-specific or broad market news
  • get_events_calendar — Earnings, dividends, splits, and IPO calendars
  • get_economic_data — Economic indicators and high-impact event tracking

Fundamental Analysis

  • fmp_fetch — Direct access to 60+ financial data endpoints (income statements, balance sheets, cash flows, key metrics, and more)
  • compare_peers — Side-by-side peer comparison across 12 financial ratios
  • get_earnings_transcript — Parsed earnings calls with speaker attribution and Q&A sections

Stock Screening & Discovery

  • screen_stocks — Screen by sector, market cap, beta, dividend, volume, and more
  • get_institutional_ownership — Institutional holder analytics and ownership trends
  • get_insider_trades — Insider transaction flow and statistics
  • get_etf_holdings — ETF/fund holdings, sector and country allocation

Technical Analysis

  • get_technical_analysis — Composite signals from 7 indicators (SMA, EMA, RSI, MACD, Bollinger, ADX, Williams %R) with buy/sell scoring

Analyst Sentiment

  • get_estimate_revisions — Historical EPS/revenue estimate revision trends
  • screen_estimate_revisions — Screen for estimate momentum across a universe of stocks

Data Discovery

  • fmp_list_endpoints — Browse all 60+ available data endpoints by category
  • fmp_describe — Get parameter documentation for any endpoint
  • fmp_search — Search for companies by name or ticker
  • fmp_profile — Company profile with sector, industry, and key stats

Install

pip install fmp-mcp

Optional estimate-revision tools (requires PostgreSQL):

pip install "fmp-mcp[estimates]"

Configuration

Set your API key:

export FMP_API_KEY="your_key"

Optional settings:

  • FMP_CACHE_DIR — Custom cache directory (default: ~/.cache/fmp-mcp/)
  • FMP_CACHE_MAXSIZE — Max in-memory cache entries (default: 200)

Run

fmp-mcp

Or use with Claude Code:

{
  "mcpServers": {
    "fmp-mcp": {
      "type": "stdio",
      "command": "uvx",
      "args": ["fmp-mcp"],
      "env": { "FMP_API_KEY": "your_key" }
    }
  }
}

How it's different

Raw API wrapper fmp-mcp
Approach Expose every endpoint 1:1 Purpose-built analytical tools
Output Raw JSON, dozens of fields Structured, summarized, analysis-ready
Composition One API call per tool Multiple sources stitched together
AI-optimized Generic descriptions Tool descriptions and schemas designed for LLM tool selection
Caching None Per-endpoint disk caching with configurable refresh strategies

Requirements

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