CrewAI MCP Demo

This repository demonstrates different approaches for using CrewAI with MCP (Model Context Protocol) to interact with external tools and services through a standardized protocol.

🌟 Featured Examples

🏭 Enterprise Regulatory Intelligence

📍 Location: scaffolding_approach_examples/snowflake_mcp_demo/

A production-ready 3-agent system that combines CrewAI's multi-agent orchestration with Snowflake's enterprise data capabilities to build regulatory intelligence systems.

Key Features:

• 🤖 3-Agent Coordination: Regulatory Intelligence + SEC Filing Analysis + Market News
• 📊 Enterprise Scale: Semantic search across 372,299 SEC filings via Snowflake MCP
• 🎯 Professional Output: Investment-grade regulatory impact reports
• 🚀 Production Ready: Complete deployment and configuration examples

→ View Detailed Tutorial

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🚀 Two Integration Approaches

This repository demonstrates two different ways to integrate CrewAI with MCP:

1. 🏗️ Scaffolding Approach (Recommended for Production)

• Uses CrewAI's project scaffolding with @CrewBase decorator
• Structured project with configuration files
• Built-in get_mcp_tools() method (CrewAI 0.134.0+)
• Better for complex, maintainable applications

Examples:

• Snowflake Enterprise Demo - Regulatory intelligence system
• Mathematician Project - Math operations via local StdIO server
• Context7 Integration - Document search via streamable-HTTP

2. 📝 Script Approach (Great for Learning/Prototyping)

• Standalone Python scripts using MCPServerAdapter directly
• Quick to set up and experiment with
• Perfect for understanding MCP concepts

Examples:

• stdio_client_demo.py - Math operations
• sse_client_demo.py - Cloudflare docs search
• streamable_http_client_demo.py - Simple greeting
• multiple_servers_client_demo.py - Combined functionality

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🔧 Transport Mechanisms

Streamable HTTP ⭐ (Recommended)

• Use case: Remote hosted servers (Context7, cloud services)
• Benefits: Simple setup, bidirectional communication, web-friendly
• Example: Snowflake MCP, Context7 API

Server-Sent Events (SSE)

• Use case: Real-time server-to-client updates
• Benefits: Good for streaming responses, widely supported
• Example: Cloudflare docs, real-time data feeds

Standard Input/Output (StdIO)

• Use case: Local development, testing, process-based servers
• Benefits: Simple local setup, no network required
• Example: Local math server, file processing tools

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📁 Project Structure

crewai-mcp-demo/
├── 🏗️ scaffolding_approach_examples/
│   ├── snowflake_mcp_demo/          # 🌟 FEATURED: Enterprise regulatory intelligence
│   ├── mathematician_project/       # Math operations via local StdIO server
│   └── crewai_context7_mcp/         # Context7 integration via streamable-HTTP
├── 📝 script_approach_examples/      # Standalone script examples
│   ├── stdio_client_demo.py         # Math operations via StdIO
│   ├── sse_client_demo.py           # Cloudflare docs via SSE
│   ├── streamable_http_client_demo.py # Greeting via HTTP
│   └── multiple_servers_client_demo.py # Multiple servers example
├── 🖥️ servers/                       # Local MCP servers
│   ├── hello_http_server.py         # HTTP greeting server
│   └── math_stdio_server.py         # StdIO math server
└── README.md                        # This file

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⚡ Quick Start

Option 1: Try the Enterprise Demo (Recommended)

cd scaffolding_approach_examples/snowflake_mcp_demo/
# Follow the detailed setup guide in that directory

Option 2: Try a Simple Script

# For math operations (local server)
python3 script_approach_examples/stdio_client_demo.py

# For Cloudflare docs (remote server)  
python3 script_approach_examples/sse_client_demo.py

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🛠️ Prerequisites

• Python: Version >= 3.10 < 3.14
• CrewAI: Version >= 0.134.0 (for scaffolding approach)
• API Keys: Depends on the example (OpenAI, Snowflake, etc.)
• uv (recommended) or pip for package management

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📚 Learn More

Featured Documentation

• 🏭 Enterprise Regulatory Intelligence Tutorial - Complete production system
• 🧮 Mathematician Project - Local MCP server integration
• 🔍 Context7 Integration - Cloud MCP service

Resources

• CrewAI Documentation
• CrewAI MCP Integration Guide
• Model Context Protocol Specification

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🤝 Contributing

Contributions welcome! Areas where we'd love help:

• Additional MCP server examples
• More transport mechanism demos
• Documentation improvements
• Bug fixes and optimizations

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📄 License

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

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⭐ Star History

Happy building with CrewAI and MCP! 🚀