The stock-analysis API you don't have to build

I was building a feature that needed to say something useful about a stock — not just print its P/E, but actually read the situation: is this cheap or expensive, what's the bull case, is the insider buying real or routine. I went looking for an API. Every finance API I found sold me raw data . Alpha Vantage, Twelve Data, Yahoo Finance, FMP — they'll hand you fundamentals, prices, filings, all of it. Great. Now I get to write the part that turns 40 metrics into "this looks expensive but the moat is widening." That's the part that's actually hard, and the part I didn't want to own forever. So I'd be wiring three data providers, normalizing their conflicting field names, writing and tuning the LLM prompts, handling the rate limits and the caching, and then maintaining all of it as the upstreams change. For a feature, not a product. What I wanted instead A single endpoint. Ticker in, analysis out — already synthesized, already structured. That's what I ended up building for myself and then put on RapidAPI: Agent Toolbelt — AI Stock Research API . It pulls live fundamentals from Polygon, Finnhub, and Financial Modeling Prep, then returns a Motley-Fool-style read as typed JSON. The numbers are in there too, but the point is the verdict and the reasoning. Here's a real stock-thesis response: { "verdict" : "bullish" , "oneLiner" : "Nvidia owns the essential infrastructure for the AI revolution with a defensible software moat." , "keyStrengths" : [ "~80%+ data center GPU market share" , "CUDA moat creates switching costs" , "42 buy / 5 hold / 1 sell analyst consensus" ], "keyRisks" : [ "36.9x P/E leaves no margin for error" , "Competition from AMD and custom silicon" ], "insiderRead" : "Two executives bought ~47k shares each — meaningful open-market purchases, not routine grants." , "dataSnapshot" : { "currentPrice" : 180.4 , "peRatio" : 36.9 , "marketCapBillions" : 4452.2 } } That's one HTTP call. No data-provider accounts, no prompt engineering, no normalization layer. The