# How to Vibe Code Your Own StocksBrew (and Stop Paying for It) > US Stock Analysis and Watchlist Tracking - Site: https://stocksbrew.online - Category: Finance & Market Intelligence SaaS - Platforms: Web app - Verdict: **Solid side project** (74/100 vibecodeable) - Estimated effort: 2-3 weeks part-time ## Verdict Build a functional personal clone of StocksBrew in a couple of weeks, though integrating reliable financial data feeds and the MCP server layer requires careful engineering. StocksBrew is a brilliant solo-dev execution combining traditional financial data APIs with AI synthesis and modern developer tooling (MCP). Vibecoding this over 2 weeks is entirely realistic if you leverage Next.js, Turso for SQLite storage, and the Anthropic API for the synthesis pipeline. The main friction points will be structuring the automated financial data ingestion cron jobs and writing the Model Context Protocol (MCP) server endpoints so your local IDE can query your private watchlist seamlessly. Since the paid tier is only $9/mo, building this is purely for education, customization, and having your own local AI agent stock research pipeline. ### What you can't replicate - The exact proprietary prompt chain and fine-tuned context aggregation of the original author - The existing subscriber network and community feedback loop ## What it does An AI-powered US stock analysis and watchlist tracking platform providing automated fundamentals, news aggregation, technical zones, and MCP/REST API access for AI coding assistants. ### Core features - Stock Search & Detailed Financial Page (valuation, filings, earnings, news) - Automated Daily Data Pipeline (pulling prices, fundamentals, earnings calendar) - Watchlist Tracking (Radar) with price level and earnings alerts - AI Synthesis Pipeline (generating Buy/Hold/Sell calls, target prices, buy/trim zones, business drivers, downside risks) - Community & Sentiment Ingestion (scraping/summarizing Reddit or market discussions) - MCP (Model Context Protocol) Server & REST API endpoints for AI IDE integration - Market Overview Dashboard (daily movers, sector performance, market daily digest) ## The business ### Pricing - Free: $0 - Pro: $9/mo Founded 2026. Team size: 1 (Solo founder). ## The hard parts - Securing reliable, low-cost US financial data pipelines for real-time prices and deep fundamental metrics without incurring enterprise API fees - Orchestrating structured LLM synthesis prompts to reliably output valid JSON schemas for stock calls, price targets, and risk factors - Implementing an MCP server architecture that securely exposes personal watchlist contexts to local LLM clients (Claude Code, Cursor) - Building robust background background cron workers for continuous market data syncing, sentiment analysis, and alert dispatching ## How to vibe code StocksBrew ### Prerequisites - Node.js (Free): Runtime environment for Next.js and TypeScript services - GitHub (Free): Source control and deployment pipeline - Anthropic API Key (Pay-as-you-go): Required for stock research synthesis and MCP context queries ### Recommended AI tools - Claude Code: Best-in-class agentic coding tool for scaffolding the Next.js app, API routes, and MCP server end-to-end. - Cursor: Ideal AI-native editor for refining UI components, charts, and Tailwind styling. ### Stack - Frontend: Next.js (App Router, Tailwind CSS, shadcn/ui) - Backend: Next.js API Routes / Server Actions & custom MCP server handler - Database: Turso (libSQL/SQLite at the edge) - Auth: better-auth - Payments: None (Personal use clone) - Other: Anthropic API, Vercel AI SDK, Financial Modeling Prep or Yahoo Finance API ### Hosting - Vercel (Hosting the Next.js frontend, API routes, and serverless background cron functions): $0-20/mo - Turso (Serverless SQLite database for watchlists, user data, and cached stock analyses): $0/mo (Free tier) ### Build guide 1. **Project Scaffolding & Database Setup** — Initialize the Next.js application with TypeScript, Tailwind CSS, and set up Turso SQLite connection with better-auth. ``` Create a new Next.js 16 app using App Router and Tailwind CSS. Configure Turso (libSQL) as the database client using Drizzle ORM or raw SQL queries. Implement better-auth for secure user authentication with email/password. Set up a clean layout featuring a top navigation bar (Market, Explore, Watchlist) and dark mode support using Tailwind. ``` 2. **Financial Data Ingestion & Stock Page UI** — Build the stock lookup page and integrate a third-party financial API to pull prices, fundamentals, earnings, and news. ``` Build a dynamic stock lookup route at /stock/[ticker]. Create server actions that fetch quote data, five-year financials, valuation metrics, and recent news from a financial API (such as Financial Modeling Prep or Yahoo Finance wrapper). Design a clean financial summary card UI showing price, daily change, valuation ratios, analyst ratings breakdown, and latest news headlines. ``` 3. **AI Synthesis Pipeline & Structured Analysis** — Implement an LLM pipeline using the Vercel AI SDK to generate structured buy/hold/sell calls, target prices, buy/trim zones, core drivers, and risk factors. ``` Implement an AI synthesis pipeline using the Vercel AI SDK and Anthropic API. When a user views a stock or triggers a refresh, gather the latest fundamentals and news, then prompt Claude to generate a structured JSON object containing: call (Buy/Hold/Sell/Watch), conviction level, target price, buy/trim zones, core business drivers, and downside risks. Render these outputs cleanly on the stock page with distinct visual badges. ``` 4. **Watchlist (Radar) & Automated Cron Alerts** — Build watchlist management and Vercel Cron jobs to check stock prices and earnings dates against user watchlists. ``` Build a Watchlist feature allowing users to add and remove stock tickers. Create a Vercel cron job that runs daily to evaluate saved watchlist tickers against current market prices and upcoming earnings dates. If a price hits a defined buy/trim zone or earnings are within 24 hours, generate an internal notification record in the database and display a notification bell badge in the user dashboard. ``` 5. **Market Overview & Sentiment Dashboard** — Create the homepage market dashboard showing top gainers/losers, sector performance, and social/news crowd sentiment summaries. ``` Build the main market dashboard view displaying: (1) Today's top movers (gainers/losers with price change badges), (2) Sector performance snapshots (Tech, Semis, Industrials, Finance), and (3) A 'What the crowd's saying' card section summarizing sentiment and news drivers for major ETFs or trending stocks (like SPY, QQQ, AMD). Ensure responsive grid layouts and smooth tab toggling. ``` 6. **MCP Server & Developer REST API Integration** — Expose custom Model Context Protocol (MCP) server endpoints and a REST API so local AI coding assistants (Claude Code, Cursor) can query user watchlist data. ``` Implement a Model Context Protocol (MCP) server endpoint and secure REST API routes within the Next.js app. The API must allow authenticated local AI coding tools (Claude Code, Cursor) with scoped API tokens to query current stock research reports, user watchlists, and active alerts. Document the configuration format so a user can easily connect their local coding environment to their personal instance. ``` ### Cost vs paying **Starting costs (one-time):** - Domain name (optional): $12/yr - Anthropic API starting credits: $10 - Total: ~$22 one-time **Ongoing costs (monthly):** - Vercel Hobby / Edge Hosting: $0-5/mo - Turso Database: $0/mo - Financial API & Anthropic API usage: $5-15/mo - Total: ~$10-20/mo - Paying for the SaaS instead: $9/mo (Pro Tier) - Build time: 25-35 hours - AI tool credits: ~$15-30 in LLM API credits during development - Break-even: Not applicable (built for learning, customization, and local AI integration) ## Sources - [StocksBrew Official Website](https://www.stocksbrew.online) - [Reddit r/SideProject - StocksBrew launch background](https://www.stocksbrew.online) - [Startup Fame - StocksBrew Review & Features](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFZsX66w-SzjZu5nkhHjA-U8gtFLjOscz-sCzL9-zkoJ0y7Sm3I6gBR0D3wcGqOZ3zl3oDYMYup0jaTpswjQ4xOuMnwXLlyV2sWPCjqD9kUCptUFeReDiaKW8-P9iiGm5kOp8R0SmJhvkNGsGtVaCFT7iw2pyo6G2Q=)