Build a stock dashboard with Emergent

What Stock Lens shows you 📊

One scrollable page per ticker, every number sitting next to a short plain-English line and a green, amber, or red flag, so you're never staring at a raw ratio wondering if it's good or bad.

What Emergent is 🧰

Emergent is an AI app builder that turns plain English into a real full-stack app. You describe what you want, and it builds the React frontend, the Python (FastAPI) backend, and the database together, as one working thing rather than a pretty page with nothing behind it. As it writes, a built-in code-review agent checks its own work, so you catch fewer bugs by hand. You own and can export the code (sync it to GitHub), and when you're happy it deploys to a live public URL in one click, with SSL. You build with Fable 5, one of the frontier models Emergent lets you pick from. Pricing is credit-based: a free tier gives you 10 credits a month to build and preview, and the Standard plan is $20/mo for 100 credits (a deployed app uses about 50 a month), with extra credits as you need them.

Build it in 6 steps 🛠

1. 🚀 Start a new project in Emergent Go to Emergent (app.emergent.sh) and open a fresh project. The free tier is plenty to build and preview.
2. 🔑 Grab a free market-data key Sign up at Financial Modeling Prep (financialmodelingprep.com). The free tier gives you around 250 calls a day and covers company fundamentals, ratios, analyst estimates, and the Altman-Z and Piotroski score endpoints this dashboard uses. Copy your API key. Optional fallback: Alpha Vantage (alphavantage.co), also free but only about 25 calls a day.
3. 📋 Paste the build prompt Copy the big prompt in the next section and send it as your very first message. It's the full spec, so Emergent gets the whole dashboard right on the first pass instead of guessing.
4. 🔒 Add your key as a server-side secret When Emergent asks, add your key as a server-side environment variable (a secret) named FMP_API_KEY. Env secrets keep your key out of the frontend and out of your code, so it can't leak to anyone who opens your app. Never hard-code the key.
5. 🧱 Let it build, then tweak in plain English Emergent wires the backend to call the API, builds the dashboard UI, and runs its code-review agent over what it wrote. Preview it, then refine by describing changes: "add a 5-year revenue chart", "make the risk score dial bigger", "group the valuation metrics together". One change per message.
6. 🌐 Deploy and start your watchlist Click deploy to get a live public URL. Type in your first tickers, add the ones you follow to your watchlist, and share the link.

The full build prompt 📋

👇 Copy this whole block and paste it into Emergent as your first message. You don't need to read every line, it's the full build manual that makes the app come out right.

Build me a full-stack stock analysis dashboard web app called "Stock Lens." A user types a ticker (like NVDA) into a search bar, hits enter, and the app pulls live fundamental and market data and renders one organized dashboard page. Use Financial Modeling Prep as the data source (free tier, 250 calls a day). Store the FMP key as a server-side secret named FMP_API_KEY, never exposed to the frontend: all data fetching goes through my backend, which calls FMP and returns clean JSON. On a ticker submit, call and merge the FMP profile, quote, ratios-ttm, key-metrics-ttm, financial-growth, 5-year income and cash-flow, analyst-estimates, price-target-consensus, grades-consensus, and score (Altman Z plus Piotroski) endpoints. Cache each ticker about 12 hours to respect the rate limit, and handle bad tickers and rate-limit errors gracefully. Render one scrollable page with titled cards: a top verdict strip (name, logo, price, today's change, a composite Risk Score dial, analyst consensus, percent upside to median target), then Company Snapshot, Valuation, Growth (with a 5-year revenue and net-income bar chart), Profitability and Returns on Capital, Financial Health, Cash and Dividends, Analyst View (price-target low, median, high plus a Buy/Hold/Sell bar), a plain-English Moat and Quality read, Key Risks, and the Composite Risk Score section. Next to every metric show a short plain-English context line and a green, amber, or red indicator (for example "P/E 22, about the S&P average", "Debt-to-equity 0.4, conservative"). Compute the composite Risk Score on the backend: score five pillars 0 to 100 (financial health 30 percent, profitability and quality 25 percent, valuation 20 percent, growth durability 15 percent, sentiment and volatility 10 percent) into a 0 to 100 quality score, then Risk Score = 10 minus floor of quality divided by 10, clamped 1 to 10 (1 means low risk, 10 means high), shown as a dial with bands and the two or three pillars driving it. Auto-generate the Moat and Key Risks text from the data with simple rules. Add a Watchlist backed by a database with lightweight email or magic-link auth so it is private and survives refresh. Design it clean, warm, and responsive, cream background with one accent color, loading skeletons, color-coded values. Deploy to a live public URL and tell me where to paste my FMP_API_KEY. If FMP is unavailable, fall back to Alpha Vantage (OVERVIEW, GLOBAL_QUOTE, INCOME_STATEMENT) with an ALPHA_VANTAGE_API_KEY server-side secret, same layout and Risk Score logic.

A few honest notes 📌

The links 🔗

🛠 Emergent: app.emergent.sh
🔑 Financial Modeling Prep (free market data): financialmodelingprep.com
🔁 Alpha Vantage (free fallback): alphavantage.co