Access Financial Data with Financial Modeling Prep
MCP server wrapping Financial Modeling Prep's API for IB analysts - company profiles, financial statements, ratios, and M&A comparable analysis.
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Why it matters
Integrate with the Financial Modeling Prep API to perform advanced financial analysis, including company profiles, financial statements, and key ratios, tailored for investment banking and M&A professionals.
Outcomes
What it gets done
Retrieve detailed company profiles and sector information.
Access income statements, balance sheets, and cash flow statements.
Extract key financial ratios and enterprise value metrics.
Search for companies by name to identify ticker symbols.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/vb-fmp-mcp-server | bash Capabilities
Tools your agent gets
Retrieves comprehensive company information including sector, industry, market cap, and description
Extracts income statements with revenue, expense, and profit metrics
Retrieves balance sheet data including assets, liabilities, and equity
Provides cash flow statements showing operating, investing, and financing activities
Retrieves financial ratios including P/E, P/B, ROE, ROA, and others
Retrieves enterprise value calculations and related metrics
Search companies by name to find ticker symbols
Overview
fmp-mcp-server MCP Server
An MCP server wrapping the Financial Modeling Prep API with seven tools for company profiles, financial statements, ratios, and enterprise value, built for investment banking and M&A analysis workflows in Claude Desktop. Use for equity research, comparable-company analysis, and M&A scenario modeling grounded in real financial data. Requires an FMP API key and both Python and Node.js installed; not a trading or execution tool.
What it does
An MCP server built specifically for Investment Banking Analysts and M&A professionals, wrapping the Financial Modeling Prep (FMP) API so Claude Desktop can perform sophisticated financial analysis from natural-language requests instead of manual spreadsheet pulls.
It exposes seven tools: get_company_profile fetches sector, industry, market cap, and description; get_income_statements retrieves revenue, expenses, and profit metrics (accepting ticker, an optional result limit defaulting to 4, and an optional period defaulting to "annual"); get_balance_sheets gets assets, liabilities, and equity data (ticker, optional limit); get_cash_flow_statements accesses operating, investing, and financing activity (ticker, optional limit); get_ratios retrieves financial ratios including P/E, P/B, ROE, and ROA (ticker only); get_enterprise_value returns enterprise value calculations and related multiples (ticker, optional limit); and search_companies_by_name looks up ticker symbols by company name.
npm install -g @vipbat/fmp-mcp-server
pip install mcp fastmcp httpx
Documented use cases go well beyond simple lookups, reflecting the M&A-analyst framing: comparing EV/EBITDA multiples across major tech companies, assessing whether a company is undervalued against sector peers, estimating pro-forma Debt/EBITDA for a hypothetical acquisition (e.g. Shopify acquiring Pinterest), estimating potential synergies from an acquisition (e.g. Twilio acquiring Freshworks), manually calculating a current EV/EBITDA multiple from retrieved enterprise value and EBITDA figures and commenting on whether it looks expensive versus historical averages, identifying midcap M&A targets in a sector based on EBITDA margins and debt levels, modeling a post-acquisition debt/EBITDA ratio for a specific cash-plus-debt-funded deal size, and assessing strategic fit between an acquirer and target based on sector overlap, size compatibility, and financial strength.
When to use - and when NOT to
Use this connector for equity research, comparable-company analysis, financial statement review, or M&A scenario modeling grounded in real FMP data - retrieving actual financials and ratios rather than having the model estimate them from training data. It requires a Financial Modeling Prep API key (obtained separately at financialmodelingprep.com) and both Python 3.8+ and Node.js 14+ installed alongside Claude Desktop, so environments without that runtime combination cannot use it. It is not a trading or portfolio-management tool - it retrieves and helps analyze fundamental company data, not live market execution.
Capabilities
Accepts a company ticker symbol or name, plus optional parameters like statement period or result count. Returns structured financial data from FMP - company profiles, financial statements, ratios, enterprise value metrics, or ticker search results - which Claude can then combine into comparable-company or M&A analysis.
How to install
Built on the Financial Modeling Prep REST API, authenticated via an FMP_API_KEY environment variable set in Claude Desktop's claude_desktop_config.json, with a Python backend using mcp, fastmcp, and httpx, distributed as an npm package (@vipbat/fmp-mcp-server) that launches via npx.
Who it's for
Investment banking analysts, M&A professionals, and equity researchers who want to pull real company financials, ratios, and enterprise value data and run comparable-company or acquisition-scenario analysis conversationally in Claude Desktop.
Source README
FMP MCP Server
An MCP (Model Context Protocol) server that provides Financial Modeling Prep API integration for Claude Desktop. Built specifically for Investment Banking Analysts and M&A professionals to perform sophisticated financial analysis using natural language.
Features
- ๐ฆ Company Profiles - Get detailed company information including sector, industry, and descriptions
- ๐ Financial Statements - Access income statements, balance sheets, and cash flow statements
- ๐ Financial Ratios - Retrieve key metrics like P/E ratio, ROE, ROA, and more
- ๐ฐ Enterprise Value - Get enterprise value calculations and multiples
- ๐ Company Search - Search for companies by name to find ticker symbols
- ๐ M&A Analysis - Perform comparable company analysis and sector valuations
**##Demo video link ** https://www.youtube.com/watch?v=XhygZz1kW_E
Prerequisites
- Python 3.8 or higher
- Node.js 14 or higher
- Claude Desktop application
- FMP API key (get one at financialmodelingprep.com)
Installation
- Install the package globally:
npm install -g @vipbat/fmp-mcp-server
- Install Python dependencies:
pip install mcp fastmcp httpx
Configuration
Add the server to your Claude Desktop configuration:
Windows
Edit %APPDATA%\Claude\claude_desktop_config.json
macOS
Edit ~/Library/Application Support/Claude/claude_desktop_config.json
Add the following to the mcpServers section:
{
"mcpServers": {
"fmp": {
"command": "npx",
"args": ["@vipbat/fmp-mcp-server"],
"env": {
"FMP_API_KEY": "your-fmp-api-key-here"
}
}
}
}
Usage
Once configured, restart Claude Desktop. You can then ask Claude to:
- "What's Apple's current P/E ratio?"
- "Show me Microsoft's income statements for the last 3 years"
- "Compare the EV/EBITDA multiples of major tech companies"
- "Analyze if Company X is undervalued compared to its sector peers"
- "What's the enterprise value of Tesla?"
- "Would AMD acquiring Marvell make sense?"
- "Estimate pro-forma Debt/EBITDA for Shopify acquiring Pinterest"
- "Estimate synergies if Twilio acquires Freshworks"
- "Retrieve the latest Enterprise Value and EBITDA for AppFolio and use it to calculate the current EV/EBITDA multiple manually. Then comment if it looks expensive or cheap versus historical averages"
- "Identify two midcap companies in the consumer discretionary sector that could be attractive M&A targets based on healthy EBITDA margins and manageable debt levels"
- "Estimate the post-acquisition debt/EBITDA ratio if Chewy (CHWY) were to acquire Five Below (FIVE) with a $2 billion cash+debt funded deal"
- "Assess whether a potential acquisition of Zynex (ZYXI) by Axon Enterprise (AXON) would make strategic sense based on sector overlap, size compatibility, and financial strength."
Available Tools
get_company_profile
Fetches comprehensive company information including sector, industry, market cap, and description.
get_income_statements
Retrieves income statements with revenue, expenses, and profit metrics.
- Parameters:
ticker(required),limit(optional, default: 4),period(optional, default: "annual")
get_balance_sheets
Gets balance sheet data including assets, liabilities, and equity.
- Parameters:
ticker(required),limit(optional, default: 4)
get_cash_flow_statements
Accesses cash flow statements showing operating, investing, and financing activities.
- Parameters:
ticker(required),limit(optional, default: 4)
get_ratios
Retrieves financial ratios including P/E, P/B, ROE, ROA, and more.
- Parameters:
ticker(required)
get_enterprise_value
Gets enterprise value calculations and related metrics.
- Parameters:
ticker(required),limit(optional, default: 4)
search_companies_by_name
Searches for companies by name to find ticker symbols.
- Parameters:
query(required)
Example Use Cases
M&A Analysis
"Analyze whether Salesforce's acquisition of Slack was overvalued based on comparable SaaS company multiples"
Sector Comparison
"Compare the median EV/EBITDA ratios in the cybersecurity sector and identify which companies are trading below sector median"
Financial Health Check
"Evaluate Microsoft's financial health using key ratios and cash flow trends"
Troubleshooting
"FMP_API_KEY environment variable is not set"
Make sure you've added your FMP API key to the Claude Desktop configuration file.
"Python not found"
Ensure Python 3.8+ is installed and available in your system PATH.
Server fails to start
Check that all Python dependencies are installed:
pip install mcp fastmcp httpx
FAQ
Common questions
Discussion
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