🎯 Structured Workflow Engine MCP Server
Context Engineering Framework with ready-to-use development workflows that bring structure to chaos.
🎯 What is this
Structured Workflow System - designed to help both high-tier and low-tier AI models follow consistent processes:
- 🧠 Context Engineering - workflows engineered for reliable AI execution across model tiers
- 🔧 9 Workflows - battle-tested processes that provide structure and guardrails
- ⚡ Smart Validation - automatically validates prerequisites and skips irrelevant steps
- 📋 12 Mini-Prompts - context-engineered prompts organized by development phases
🚀 Installation
# 1. Clone repository
git clone https://github.com/your-repo/agents-playbook
cd agents-playbook
# 2. Install dependencies
npm install
# 3. Add OpenAI API key to .env
OPENAI_API_KEY=your_key_here
# 4. Generate search index
npm run build:embeddings
# 5. Start server
npm run dev
MCP Server:
- Local Development: http://localhost:3000/api/mcp
- Production: https://agents-playbook.vercel.app/api/mcp
🧪 Testing
# MCP Inspector for testing
DANGEROUSLY_OMIT_AUTH=true npx @modelcontextprotocol/inspector@latest http://localhost:3000/api/mcp
# Run tests (90+ tests)
npm run test:integration
get_available_workflows
Search workflows with AI semantic search.
Example:
- Input:
"fix critical bug" - Output:
quick-fix workflow (🎯 89% match)
select_workflow
Get complete workflow with execution plan.
get_next_step
Step-by-step navigation with smart validation.
📁 Workflows (9 total)
🚀 Development (4)
- feature-development - Complete feature development lifecycle
- product-development - From idea to product launch
- quick-fix - Fast bug fixes and hotfixes
- code-refactoring - Code architecture improvements
🧪 Testing & QA (3)
- fix-tests - Systematic test failure diagnosis and repair with refactoring integration
- fix-circular-dependencies - Comprehensive circular dependency resolution with architectural refactoring
- unit-test-coverage - Comprehensive unit test coverage improvement
📋 Setup & Planning (2)
- project-initialization - New project setup
- trd-creation - Technical Requirements Document creation
🎯 Usage Examples
1. Search: "create new feature"
2. Result: feature-development workflow (🎯 92% match)
3. Execute: 14 steps with TRD integration and smart skipping
1. Search: "improve test coverage"
2. Result: unit-test-coverage workflow (🎯 94% match)
3. Execute: 7 steps of systematic coverage improvement
1. Search: "circular dependencies"
2. Result: fix-circular-dependencies workflow (🎯 95% match)
3. Execute: 7 steps of dependency resolution with refactoring integration
1. Search: "technical documentation"
2. Result: trd-creation workflow (🎯 94% match)
3. Execute: 7 steps of TRD creation with validation
🔌 MCP Integration
🤖 Claude Desktop
{
"mcpServers": {
"agents-playbook": {
"url": "https://agents-playbook.vercel.app/api/mcp"
}
}
}
🎯 Cursor
Add to your Cursor settings or create a MCP configuration:
{
"mcpServers": {
"agents-playbook": {
"url": "https://agents-playbook.vercel.app/api/mcp",
"description": "AI Agent Workflow Engine with semantic search"
}
}
}
For Cursor users:
- Open Cursor Settings
- Navigate to "Extensions" or "Integrations"
- Add MCP Server configuration
- Restart Cursor
📁 Direct File Usage (Any IDE)
Copy playbook files directly to your project:
# Copy entire playbook to your project
cp -r public/playbook/ /path/to/your/project/
# For Cursor: create a .cursorrules file
echo "Use workflows from playbook/ directory for structured development" > .cursorrules
📚 Local Usage
# Copy entire playbook to your project
cp -r public/playbook/ /path/to/your/project/
# For Cursor: create a .cursorrules file
echo "Use workflows from playbook/ directory for structured development" > .cursorrules
Benefits:
- ✅ Works without MCP server
- ✅ Customize for your team
- ✅ Offline access
- ✅ Version control with project
- ✅ Cursor can reference workflows directly
🧠 How it works
- Context Engineering - workflows designed with clear context boundaries and validation
- Semantic Search - OpenAI embeddings understand task context for workflow selection
- YAML Workflows - structured processes with phases, steps, and guardrails
- Mini-Prompts - context-engineered reusable prompts that work across model tiers
- Smart Validation - prevents execution without required context, provides structure for low-tier models
🐛 Troubleshooting
"No workflows found"
- Use simple terms: "bug", "feature", "documentation"
- Check:
npm run build:embeddings
"OpenAI API errors"
- Check
OPENAI_API_KEY in .env - System falls back to text search if OpenAI unavailable
"Can't connect to MCP server"
- Make sure server is running:
npm run dev - URL:
http://localhost:3000/api/mcp
"Steps are being skipped"
- This is normal behavior! System skips steps without required context
- Check logs to understand skip reasons
🎯 Structured Workflow Engine - Context engineering framework that brings order to chaos in AI-driven development