In a recent AI hackathon, I built Stock Sage — an AI-powered stock analysis platform that brings together technical indicators, news sentiment, and options strategy exploration. The secret sauce was Kiro IDE's Model Context Protocol (MCP), which turned research, architecture and coding into a single conversational workflow. Let me walk you through how it all came together. ✨
🔥 1. Kiro's MCP: Your AI Toolkit on Steroids
What's MCP? It's how Kiro connects to real-world tools — search engines, GitHub, and even your local filesystem — so it can research, code, and document inside the IDE.
🎯 Core Capabilities
| Feature | Description | Power Level |
|---|---|---|
| 🌐 Knowledge Access | Access knowledge bases & docs | ⭐⭐⭐⭐⭐ |
| 🔌 API Integration | Integrate APIs & services | ⭐⭐⭐⭐⭐ |
| 🧰 Domain Tools | Use domain-specific tools | ⭐⭐⭐⭐ |
| 💾 File System | Interact with files and databases | ⭐⭐⭐⭐⭐ |
🛠️ Configuration Magic
📂 .kiro/mcp.json configuration
{
"mcpServers": {
"web-search": {
"args": ["mcp-server-brave-search@latest"],
"env": { "BRAVE_API_KEY": "YOUR_BRAVE_KEY" }
},
"github-tools": {
"args": ["mcp-server-github@latest"],
"env": { "GITHUB_PERSONAL_ACCESS_TOKEN": "YOUR_GITHUB_TOKEN" }
},
"filesystem": {
"args": ["mcp-server-filesystem@latest"]
}
}
}
🔥 Power Tools Breakdown:
- 🌟 Brave Search: Instant web research for analysis techniques, UI patterns, and best practices
- ⚡ GitHub Tools: Pull FinBERT examples, indicator libraries and implementation patterns
- 🗂️ Filesystem: Give Kiro project context so generated code stays consistent
- 💡 Pro tip: Keep your MCP context file under version control (without keys) and add the secrets via environment variables in CI/CD.
🏗️ 2. Building with Specs — Not "Wing It"
📋 The Spec-First Philosophy
I used a spec-first approach: write feature specs, ask Kiro to expand them into architecture, data flows, and implementation tasks. Kiro suggested a scalable layout:
- React frontend — dashboards, charts, options explorer
- FastAPI backend — sentiment, fundamentals, technical analysis, caching
- MongoDB — user profiles and metadata
- Supabase — market data caching & sync layer
⚡ 3. Feature Highlights — AI + MCP Collaboration
🎪 Kiro translated specs into working modules and documentation
🔍 News Sentiment (FinBERT)
📰 News Sources → 🧹 Filter Noise → 🤖 FinBERT → 📊 Sentiment Scores
What it does: Scrapes multiple sources, filters promotional noise, runs FinBERT, and emits sentiment scores with confidence metrics.
💰 Fundamental Analysis Engine
🏢 Company Data → 📊 Ratio Calculations → 📈 Growth Analysis → 🎯 Value Scoring
What it does: Processes financial statements, calculates key ratios (P/E, P/B, ROE, Debt-to-Equity), analyzes revenue/earnings growth patterns, and generates comprehensive fundamental health scores.
📈 Advanced Technical Analysis
📊 Market Data → 🔄 Multi-Timeframe → 🎯 Pattern Recognition → ⚡ Smart Signals
What it does: Implements advanced indicators beyond basic RSI/MACD — including Ichimoku clouds, Fibonacci retracements, volume profile analysis, and custom momentum oscillators for sophisticated technical insights.
🎯 Signals Dashboard
What it does: Aggregates technicals (RSI, MACD, Bollinger etc) + sentiment to produce prioritized signals.
🔐 Authentication & Profiles
- 🔑 Google OAuth - Seamless sign-in
- 👤 Profile Onboarding - Personalized experience
- 💎 Premium Views - Protected advanced features
🚧 4. Challenges & How Kiro Helped Solve Them
🎯 Challenge-Solution Matrix
🚨 Challenge
💡 Kiro's Solution
📈 Impact
🚫 API Blocking
Yahoo Finance blocked cloud IPs
🔄 Smart Caching
Supabase cache + sync scripts
📊 Results
- ✅ 99.9% uptime
- ⚡ 3x faster responses
- 💰 Lower API costs
🐌 Slow FinBERT
Sentiment analysis bottleneck
⚡ Concurrency Magic
ThreadPoolExecutor + batching
📊 Results
- 🚀 10x processing speed
- 📱 Real-time sentiment
- 🎯 Better UX
📱 Mobile UX Issues
Wide tables on small screens
🎨 Responsive Cards
Card-based + horizontal scroll
📊 Results
- 📱 Mobile-first design
- 👆 Touch-friendly
- 📊 Better engagement
🎯 5. Why Stock Sage Matters (For Analysts & Investors)
🎪 Analysis-First, Not Execution
Stock Sage focuses on analysis — not execution
🚀 Value Proposition
🎯 For Analysts
- 📊 Unified Dashboard — All tools in one place
- ⚡ AI Insights — FinBERT sentiment + confidence
- 📱 Mobile Ready — Analysis on-the-go
- 🔐 Secure Access — OAuth-protected workspace
💼 For Investors
- 🎪 Strategy Explorer — Test options without risk
- 📈 Technical Signals — RSI, MACD, Bollinger aggregated
- 📰 Sentiment Analysis — News impact quantified
- 🎯 Priority Signals — Focus on what matters
- 💰 Fundamental Metrics — P/E, ROE, growth trends analyzed
💭 Final Thoughts
Built in 10 days, Stock Sage shows how an MCP-enabled AI assistant can amplify a single developer into a multidisciplinary team: research, architecture, implementation and documentation — all inside the IDE.
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