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Use read-only FMP data to build earnings evidence packs and catalyst scores.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "fmp-mcp-research" yet — see the docs or source repo.
Using read-only FMP data, create a buy-side earnings-call evidence pack for Apple’s latest quarter. Include revenue, margins, segment performance, management guidance, valuation takeaways, and key risks, and cite the supporting data for each conclusion.
A structured evidence pack summarizing key conclusions, financial data, and risks with clear data-backed support.
Create a catalyst scoring report for Nvidia over the next two quarters using readable FMP financial and valuation data. Score growth trend, profitability, expectation gap, and valuation sensitivity, then provide a total score with brief rationale.
A multidimensional scoring report with category scores, total score, key drivers, and a concise conclusion.
Using FMP data, compare Tesla, Ford, and General Motors across the last four quarters on revenue growth, gross margin, free cash flow, and valuation multiples. Output a research-ready table and three insights.
A discussion-ready comparison table plus three distilled insights on key differences and implications.
Access financial data and analysis tools for faster research and modeling.
Access stock quotes, financial metrics, risk data, and news sentiment.
Access Financial Modeling Prep stable API for stocks, filings, and market data.
Fetch public company financial statements for analysis without an API key.
Find and compare MCP servers for AI finance agent workflows.
Access stock quotes, historical data, and technical indicators through MCP.