by imbenrabi
A Model Context Protocol (MCP) implementation for Financial Modeling Prep, enabling AI assistants to access and analyze financial data, stock information, company fundamentals, and market insights.
Requires a passing catalog security scan. Resolve the flagged issues and resubmit to enable featuring.
# Add to your Claude Code skills
git clone https://github.com/imbenrabi/Financial-Modeling-Prep-MCP-ServerGuides for using ai agents skills like Financial-Modeling-Prep-MCP-Server.
Last scanned: 5/30/2026
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}A Model Context Protocol (MCP) server for the Financial Modeling Prep API, exposing 250+ financial data tools to AI assistants.
No installation required. Connect directly:
https://financial-modeling-prep-mcp-server-production.up.railway.app/mcp
Provide your FMP_ACCESS_TOKEN in session configuration and start using 5 meta-tools to load toolsets on demand.
npx financial-modeling-prep-mcp-server --fmp-token=YOUR_FMP_API_KEY
Or install globally:
npm install -g financial-modeling-prep-mcp-server
fmp-mcp --fmp-token=YOUR_FMP_API_KEY
Get your API key at financialmodelingprep.com.
Prerequisites: Node.js 25.3.0 or higher (for v2.6.0+). For older versions (v2.5.x and below), Node.js 20+ is required.
Choose the method that fits your workflow:
npm install -g financial-modeling-prep-mcp-servernpm install && npm run buildSee docs/INSTALLATION.md for detailed steps per method.
The server supports three operational modes controlled via CLI arguments, environment variables, or session configuration:
| Mode | How to Enable | Description |
|---|---|---|
| Dynamic | DYNAMIC_TOOL_DISCOVERY=true |
Starts with 5 meta-tools; load toolsets at runtime |
| Static | FMP_TOOL_SETS=search,company |
Pre-loads specified toolsets on session creation |
| All Tools (default) | (default) | Loads all 250+ tools immediately |
Precedence: CLI args > Environment variables > Session config > Defaults.
See docs/CONFIGURATION.md for the full configuration reference.
Connect to the server via HTTP/SSE transport:
/mcp with mcp-client-id headerSee docs/USAGE.md for client-specific setup, session headers, and request examples.
24 categories covering:
Search · Directory & Symbol Lists · Company Information · Financial Statements · Financial Metrics & Analysis · Technical Indicators · Quotes & Price Data · Market Indexes & Performance · Market Data · News & Press Releases · SEC Filings · Insider & Institutional Trading · ETFs & Funds · Government Trading · Cryptocurrency & Forex · Earnings · Special Data Sets · Commodities · Economics · Bulk Data Tools
See docs/API_REFERENCE.md for the complete tool catalog.
This server is listed on multiple MCP registries for easy discovery:
See docs/REGISTRIES.md for registry-specific setup instructions.
Contributions are welcome. Please see CONTRIBUTING.md for development setup, testing, and pull request guidelines.
Financial-Modeling-Prep-MCP-Server is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by imbenrabi. A Model Context Protocol (MCP) implementation for Financial Modeling Prep, enabling AI assistants to access and analyze financial data, stock information, company fundamentals, and market insights. It has 139 GitHub stars.
Financial-Modeling-Prep-MCP-Server returned warnings in SkillsLLM's automated security scan. It has no critical vulnerabilities, but review the flagged issues in the Security Report section before adding it to your workflow.
Clone the repository with "git clone https://github.com/imbenrabi/Financial-Modeling-Prep-MCP-Server" and add it to your Claude Code skills directory (see the Installation section above).
Financial-Modeling-Prep-MCP-Server is primarily written in TypeScript. It is open-source under imbenrabi on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh Financial-Modeling-Prep-MCP-Server against similar tools.
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