DocAgent - AI-Powered Document Generation Suite

AI-powered document generation suite with LangGraph workflows and Cursor IDE integration via MCP (Model Context Protocol)

DocAgent is a comprehensive document generation system that creates professional software documentation using AI. It integrates seamlessly with Cursor IDE through MCP servers and supports 12 different document types with orchestrated workflows.

🚀 Features

Document Types

• 📋 Business Requirements (BRD/PRD) - Product and business requirement documents
• ⚙️ Functional Requirements (FRD) - Detailed functional specifications
• 🏗️ System Requirements (SRD) - System architecture and requirements
• 🧪 Technical Requirements (TRD/TDD) - Technical design and test documents
• 🗄️ Database Design (ERD/API) - Entity relationship diagrams and API specs
• 🎨 UI/UX Design - Wireframes and design system documentation
• 📊 Project Planning - Project plans and milestone tracking
• ✅ Test Strategy - Comprehensive testing documentation
• 🚀 CI/CD Documentation - Deployment and environment setup
• 📦 Release Runbooks - Release procedures and rollback plans

Core Capabilities

• 🔄 LangGraph Workflows - Parallel document generation with conditional logic
• 🎯 Smart Orchestration - Profile-based generation (Full, Lean, Tech-only, PM-only)
• 💻 Cursor IDE Integration - Native MCP server integration
• 🛡️ Safe File Operations - Collision detection and backup systems
• 📝 Jinja2 Templates - Customizable document templates
• ⚡ FastMCP v2 - Modern MCP protocol implementation
• 🔧 CLI Tools - Command-line interface for batch operations

📦 Installation

Prerequisites

• Python 3.9+
• Cursor IDE
• Git

Quick Setup

# Clone the repository
git clone https://github.com/vinnyfds/docagent.git
cd docagent

# Install dependencies
pip install -r requirements.txt

# Create environment file
cp .env.template .env
# Edit .env with your API keys

# Verify installation
python scripts/verify_mcp.py

Cursor IDE Integration

# Install FastMCP
pip install fastmcp

# The MCP servers will be automatically configured in Cursor
# Restart Cursor to load the DocAgent tools

🎯 Quick Start

Using Cursor IDE (Recommended)

1. Open any file in Cursor
2. Type / to open command palette
3. Look for DocAgent tools:
   • ping() - Health check
   • generate_all() - Generate all documents
   • orchestrate_docgen() - Profile-based generation

Using CLI

# Generate all documents
python scripts/cli_generate.py --idea tests/fixtures/idea_sample.json --all

# Generate specific documents
python scripts/cli_generate.py --idea my_idea.json --docs brd_prd frd srd

# Use orchestration profiles
python -c "
from orchestrator.graph import orchestrate_docgen
from docs_agent.state import Idea
import json

with open('tests/fixtures/idea_sample.json') as f:
    data = json.load(f)
    idea = Idea(**data)
    
result = orchestrate_docgen(idea, profile='lean', overwrite=False)
print('Generated:', result)
"

🏗️ Architecture

System Overview

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   Cursor IDE    │◄──►│  FastMCP Server  │◄──►│  LangGraph      │
│                 │    │                  │    │  Workflow       │
│ - Command Palette│    │ - DocGenAgent    │    │                 │
│ - Tools Integration │  │ - Orchestrator   │    │ - Parallel Nodes│
│ - MCP Protocol  │    │ - Tool Registry  │    │ - Conditional   │
└─────────────────┘    └──────────────────┘    └─────────────────┘
                                │
                                ▼
                       ┌──────────────────┐
                       │  Document Engine │
                       │                  │
                       │ - Jinja2 Templates│
                       │ - Safe File Ops  │
                       │ - Output Manager │
                       └──────────────────┘

Project Structure

docagent/
├── docs_agent/              # Core document generation agent
│   ├── __init__.py         # Package initialization
│   ├── state.py            # Pydantic models (Idea, Context, DocRequest)
│   ├── graph.py            # LangGraph workflow definition
│   ├── server.py           # FastMCP server implementation
│   ├── nodes/              # Document generation nodes
│   │   ├── brd_prd.py      # Business requirements
│   │   ├── frd.py          # Functional requirements
│   │   ├── srd.py          # System requirements
│   │   └── ...             # Other document types
│   ├── prompts/            # Jinja2 templates
│   │   ├── brd_prd.md.jinja
│   │   ├── openapi.yaml.jinja
│   │   └── ...
│   └── utils/              # Utilities
│       ├── render.py       # Template rendering
│       └── safety.py       # Safe file operations
├── orchestrator/           # Orchestration layer
│   ├── graph.py            # Orchestration logic
│   └── server.py           # Orchestrator MCP server
├── scripts/                # CLI and utilities
│   ├── cli_generate.py     # Command-line interface
│   ├── verify_mcp.py       # Installation verification
│   └── test_mcp_servers.py # Server testing
├── tests/                  # Test suite
│   └── fixtures/           # Test data
│       └── idea_sample.json
├── outputs/                # Generated documents
├── .cursor_rules           # Cursor IDE guardrails
├── requirements.txt        # Python dependencies
├── .env.template          # Environment template
└── README.md              # This file

🎮 Usage Examples

Idea Structure

{
  "title": "E-commerce Platform",
  "description": "Modern e-commerce platform with AI recommendations",
  "context": {
    "domain": "E-commerce",
    "stakeholders": ["Product Manager", "Engineering Team", "UX Designer"],
    "timeline": "6 months",
    "budget": "$500K"
  },
  "personas": [
    {"name": "Customer", "description": "Online shoppers"},
    {"name": "Admin", "description": "Platform administrators"}
  ],
  "modules": [
    {"name": "User Management", "description": "User registration and profiles"},
    {"name": "Product Catalog", "description": "Product browsing and search"},
    {"name": "Shopping Cart", "description": "Cart and checkout functionality"}
  ],
  "entities": [
    {"name": "User", "fields": ["id", "email", "profile"]},
    {"name": "Product", "fields": ["id", "name", "price", "inventory"]}
  ],
  "apis": [
    {"name": "User API", "methods": ["GET", "POST", "PUT", "DELETE"]},
    {"name": "Product API", "methods": ["GET", "POST", "PUT"]}
  ]
}

Orchestration Profiles

PROFILES = {
    "full": [
        "brd_prd", "frd", "srd", "trd_tdd", "erd_api", 
        "ui_wireframes", "project_plan", "test_strategy", 
        "cicd_env", "release_runbook"
    ],
    "lean": ["brd_prd", "frd", "srd", "erd_api"],
    "tech_only": ["srd", "trd_tdd", "erd_api", "cicd_env"],
    "pm_only": ["brd_prd", "project_plan", "test_strategy", "release_runbook"]
}

🛠️ Development

Running Tests

# Run verification tests
python scripts/verify_mcp.py

# Test MCP servers
python scripts/test_mcp_servers.py

# Generate sample documents
python scripts/cli_generate.py --idea tests/fixtures/idea_sample.json --all

Code Quality

# Install development dependencies
pip install ruff pytest

# Run linting
ruff check .

# Run tests
pytest -v

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

🔧 Configuration

Environment Variables

# Required
OPENAI_API_KEY=your_openai_api_key_here

# Optional
DOCGEN_BUCKET=your_s3_bucket_for_outputs
ALLOW_OVERWRITE=false
LOG_LEVEL=INFO
ENVIRONMENT=development
MCP_HOST=localhost
MCP_PORT=3000

Cursor MCP Setup

The MCP servers are automatically configured for Cursor IDE. Manual configuration:

{
  "mcpServers": {
    "DocGenAgent": {
      "command": "cmd",
      "args": ["/c", "python", "docs_agent/server.py"],
      "cwd": "/path/to/docagent"
    },
    "DocGenOrchestrator": {
      "command": "cmd", 
      "args": ["/c", "python", "orchestrator/server.py"],
      "cwd": "/path/to/docagent"
    }
  }
}

📚 Documentation

• Installation Guide
• MCP Setup Guide
• Template Customization
• AWS Deployment
• API Reference

🚀 Deployment

AWS Lambda (Coming Soon)

# Package for serverless deployment
npm install -g serverless
serverless deploy

Docker

# Build container
docker build -t docagent .

# Run container
docker run -p 3000:3000 docagent

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

Contributors

• @vinnyfds - Creator & Maintainer

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• LangGraph - Workflow orchestration
• FastMCP - MCP server framework
• Cursor IDE - AI-powered development environment
• Jinja2 - Template engine

📧 Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Email: vinnyfds@gmail.com

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🎯 Transform your ideas into comprehensive documentation with AI-powered precision!