swarms/examples/mcp_example/presentation_script.md

MCP Integration Demo Script

1. Setup & Architecture Overview

# Terminal 1: Start Stock Server
python examples/mcp_example/mock_stock_server.py

# Terminal 2: Start Math Server
python examples/mcp_example/mock_math_server.py

# Terminal 3: Start Multi-Agent System
python examples/mcp_example/mock_multi_agent.py

2. Key Components

Server-Side:

• FastMCP servers running on ports 8000 and 8001
• Math Server provides: add, multiply, divide operations
• Stock Server provides: price lookup, moving average calculations

Client-Side:

• Multi-agent system with specialized agents
• MCPServerSseParams for server connections
• Automatic task routing based on agent specialization

3. MCP Integration Details

Server Implementation:

# Math Server Example
from fastmcp import FastMCP

mcp = FastMCP("Math-Server")

@mcp.tool()
def add(a: int, b: int) -> int:
    """Add two numbers together"""
    return a + b

Client Integration:

from swarms.tools.mcp_integration import MCPServerSseParams

# Configure MCP server connection
server = MCPServerSseParams(
    url="http://0.0.0.0:8000",
    headers={"Content-Type": "application/json"}
)

# Initialize agent with MCP capabilities
agent = Agent(
    agent_name="Calculator",
    mcp_servers=[server],
    max_loops=1
)

4. Demo Flow

1. Math Operations:

Enter a math problem: 5 plus 3
Enter a math problem: 10 times 4

2. Stock Analysis:

Enter a math problem: get price of AAPL
Enter a math problem: calculate moving average of [10,20,30,40,50] over 3 periods

5. Integration Highlights

1. Server Configuration:

• FastMCP initialization
• Tool registration using decorators
• SSE transport setup

2. Client Integration:

• MCPServerSseParams configuration
• Agent specialization
• Task routing logic

3. Communication Flow:

• Client request → Agent processing → MCP server → Response handling

4. Error Handling:

• Graceful error management
• Automatic retry mechanisms
• Clear error reporting

6. Code Architecture

Server Example (Math Server):

@mcp.tool()
def add(a: int, b: int) -> int:
    """Add two numbers together"""
    return a + b

Client Example (Multi-Agent):

calculator = MathAgent("Calculator", "http://0.0.0.0:8000")
stock_analyst = MathAgent("StockAnalyst", "http://0.0.0.0:8001")

7. Key Benefits

1. Modular Architecture
2. Specialized Agents
3. Clean API Integration
4. Scalable Design
5. Standardized Communication Protocol
6. Easy Tool Registration
7. Flexible Server Implementation

8. Testing & Validation

1. Basic Connectivity:

def test_server_connection():
    params = {"url": "http://0.0.0.0:8000"}
    server = MCPServerSse(params)
    asyncio.run(server.connect())
    assert server.session is not None

2. Tool Execution:

def test_tool_execution():
    params = {"url": "http://0.0.0.0:8000"}
    function_call = {
        "tool_name": "add",
        "arguments": {"a": 5, "b": 3}
    }
    result = mcp_flow(params, function_call)
    assert result is not None