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Emma Xiang
Emma Xiang

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How I Built a Production MCP Server with Kiro

#kiro #ai #mcp

How I Built a Production MCP Server with Kiro IDE

TL;DR: I built FeedMob AdPilot, a production-ready MCP server with 6 AI-powered tools, interactive UI components, and PostgreSQL persistence using Kiro IDE. This is the story of how Specs, Steering Docs, Agent Hooks, and MCP integration transformed my development workflow.

🎯 The Challenge

Creating effective advertising campaigns requires expertise across multiple domains—understanding audiences, crafting copy, designing visuals, and optimizing for platforms. I wanted to build an AI system that could handle this entire workflow conversationally.

The technical challenge? Stitching together technologies that weren't designed to work together:

  • FastMCP for the MCP server
  • @mcp-ui/server for interactive components
  • Claude Agent SDK for AI processing
  • PostgreSQL for data persistence
  • Next.js for the client UI

🏗️ What I Built

FeedMob AdPilot transforms natural language campaign descriptions into complete advertising assets:

  1. Parse Requirements → Extract campaign parameters from conversation
  2. Conduct Research → Generate comprehensive market reports
  3. Generate Copy → Create platform-optimized variations
  4. Generate Images → Produce visual concepts
  5. Create Mixed Media → Combine assets into final creatives
  6. Campaign Management → Store everything in PostgreSQL

Live Demo: https://sc80sggw884kw448kc0sckw0.coolify-dev-pa.tonob.net/

🎨 The Kiro Difference

Spec-Driven Development (10 Features)

I created formal specifications with three documents each:

.kiro/specs/generate-ad-copy/
├── requirements.md    # User stories + acceptance criteria
├── design.md          # Architecture + correctness properties
└── tasks.md           # Implementation checklist
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Impact: Every line of code traces back to a requirement. Zero missed edge cases.

Steering Documents (7 Persistent Contexts)

I taught Kiro once through always-included docs:

  • tech.md - Technology stack and commands
  • fastmcp-integration.md - FastMCP patterns
  • mcp-ui-integration.md - UI component creation
  • agent-tool-patterns.md - Claude SDK integration
  • claude-agent-skills.md - Agent skill development
  • color-guidelines.md - Design system

Impact: Saved 8+ hours of repetitive context across 100+ conversations.

Agent Hooks (4 Automated Workflows) 

{
  "name": "Security Pre-Commit Scanner",
  "when": { "type": "fileEdited", "patterns": ["**/*"] },
  "then": {
    "type": "askAgent",
    "prompt": "Scan for API keys, tokens, credentials..."
  }
}
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Hooks I automated:

  1. Security scanning on every file edit
  2. MCP-UI docs checker for API changes
  3. MCP builder guidance for server files
  4. Agent skill builder for new tools

Impact: Prevented 3+ major bugs before they reached production.

MCP Integration (6 Servers)

Extended Kiro with specialized capabilities:

  • mcp-ui-docs - Always-current mcp-ui documentation
  • agent-skills - Skill creator and MCP builder
  • context7 - Instant library docs (FastMCP, Zod)
  • exa - Code examples and patterns
  • fetch - External documentation
  • sequential-thinking - Complex problem decomposition

Impact: The mcp-ui-docs server alone saved days of debugging outdated APIs.

💡 The Most Impressive Moment

I told Kiro:

"Create a new MCP tool for generating ad images based on the pattern in #File src/tools/generate-ad-copy.ts"

Kiro generated in ONE response:

  • ✅ Complete Zod schema with validation
  • ✅ Agent service with Claude SDK integration
  • ✅ UI factory with interactive components
  • ✅ Error handling with all edge cases
  • ✅ Proper FastMCP registration

It understood the entire project pattern from steering docs—no repeated explanations needed.

🎭 The Frankenstein Architecture

This project is a Frankenstein's monster in the best way—incompatible technologies brought to life:

┌─────────────────────────────────────────┐
│  MCP Tools (FastMCP)                    │
│  - parseAdRequirements                  │
│  - conductAdResearch                    │
│  - generateAdCopy                       │
│  - generateAdImages                     │
└──────────────┬──────────────────────────┘
               │
┌──────────────▼──────────────────────────┐
│  Agent Services (Claude Agent SDK)      │
│  - 6 specialized agents                 │
│  - Custom skill plugins                 │
└──────────────┬──────────────────────────┘
               │
┌──────────────▼──────────────────────────┐
│  UI Factories (mcp-ui)                  │
│  - Interactive components               │
│  - Real-time updates                    │
└──────────────┬──────────────────────────┘
               │
┌──────────────▼──────────────────────────┐
│  Data Layer (PostgreSQL)                │
│  - Campaign persistence                 │
└─────────────────────────────────────────┘
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🚧 Real Challenges I Faced

  1. Gateway Timeouts: Long-running AI operations hitting limits
  2. Tool Call Timeouts: Optimizing agent processing times
  3. Docker Dependencies: Image generation missing libraries
  4. Chatbot Compatibility: Existing mcp-ui clients didn't work—built custom Next.js interface
  5. Agent Skill Design: Getting consistent JSON output from LLMs

Each challenge was solved through iterative fixes with Kiro's help.

📊 By The Numbers

  • 🎯 6 MCP tools built and deployed
  • 🤖 6 agent services with custom skills
  • 📝 10 formal specs with complete traceability
  • 📚 7 steering docs for persistent context
  • 🪝 4 agent hooks for automated workflows
  • 🔌 6 MCP servers integrated
  • ⏱️ 6 days from concept to production
  • 💬 100+ conversations with Kiro

🎓 What I Learned

1. Hybrid Vibe + Spec Wins

Spec Mode for complex features → Structure, traceability, testing
Vibe Mode for iterations → 10x faster bug fixes and adjustments

Neither alone is optimal. The combination is magic.

2. Steering Docs Are Superpowers

Teaching Kiro once vs. teaching it every conversation:

  • Before: 5 minutes/conversation × 100 = 500 minutes wasted
  • After: 0 minutes repetition = 8+ hours saved

3. MCP Integration Enables The Impossible

Without mcp-ui-docs, I would have:

  • Manually searched documentation
  • Used outdated API patterns
  • Spent days debugging production issues

With it: Zero breaking changes, always-current APIs.

4. Hooks Catch Issues Early

The Security Pre-Commit Scanner found issues immediately, not in code review days later.

🚀 What's Next

Immediate priorities:

  • Fix gateway timeout issues
  • Optimize agent processing times
  • Complete Docker image generation setup

Future features:

  • Video ad generation for TikTok/Reels
  • A/B testing integration
  • Multi-platform campaigns
  • Real-time analytics
  • Template library

🏁 Final Thoughts

Kiro isn't just an AI coding assistant. It's a development environment where AI understands your project deeply and assists at every stage—from requirements to deployment.

The combination of:

  • ✅ Specs for structured planning
  • ✅ Steering for persistent context
  • ✅ Hooks for automation
  • ✅ MCP for extended capabilities
  • ✅ Vibe for natural iteration

...enabled me to build in 6 days what would have taken 2+ months traditionally.

This isn't incremental improvement. This is transformation.

🔗 Links

Built for Kiroween 2025 🎃

What's your experience with AI-assisted development? Have you tried spec-driven development with AI? Drop your thoughts in the comments! 👇

kiro #mcp #ai #devtools #hackathon #fastmcp #claude

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