get_company_profileLABSCO SUMMARY
The whole statement set, without a data export.
Ratios and a valuation are only worth something next to the statements they came from. Eight tools put profile, quote, statements, metrics and DCF in one thread, which is where the comparison between two companies actually happens.
What it is
A Python MCP server over the Financial Modelling Prep API, covering company profiles, quotes, statements, ratios, key metrics, DCF valuation and sector performance. It also ships prompts for financial analysis, investment research and sector comparison.
What you get
- Company profile and a real-time quote
- Income statement, balance sheet and cash flow data
- Key metrics and the full ratio set used for analysis
- A discounted cash flow valuation
- Companies found by name or symbol
- Sector performance across the market
- Market sectors, company profiles and statements also exposed as MCP resources
Requirements
An API key from Financial Modelling Prep, passed as FMP_API_KEY. Run it with uv (uv run python -m fmp_mcp_server.server), or from the published image ghcr.io/ccdatatraits/fmp-mcp-server:latest with an env file.
Setup effort
One command plus a key — docker run --env-file .env ghcr.io/ccdatatraits/fmp-mcp-server:latest, then supply credentials
USE CASES
01
Getting up to speed on a company
Find it by name or ticker and read the profile before anything else.
02
Reading the financials properly
Income statement, balance sheet and cash flow with the key metrics alongside them.
03
Comparing two companies on the same basis
Pull the same ratio set for both, so the comparison is like for like rather than two different screenshots.
04
Putting a number on what it is worth
Run the discounted cash flow valuation and read it against the current price.
05
Working out whether it is the company or the sector
Check sector performance before concluding anything from a single company's move.
8 tools
Listed in project docs. Your client may show a different list.
get_stock_quoteget_financial_statementsget_key_metricsget_financial_ratiosget_dcf_valuationsearch_companiesget_sector_performanceBEFORE YOU INSTALL
What to know first
Tools you get
8 tools named in the project's documentation.
Requires
- uv on PATH
- FMP_API_KEY in your environment
Where it runs
The documented client runs the server on your machine.
INSTALLATION
Connect your client
Server setup
TERMINAL
docker run --env-file .env ghcr.io/ccdatatraits/fmp-mcp-server:latestMCP Clients
Claude Code
CLAUDE CODE · JSON
{
"mcpServers": {
"fmp": {
"command": "uv",
"args": [
"run",
"python",
"-m",
"fmp_mcp_server.server"
],
"env": {
"FMP_API_KEY": "<YOUR_FMP_API_KEY>"
}
}
}
}
