Assistant checkpoint: Updated presentation script with MCP integration details

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- examples/mcp_example/presentation_script.md: Update presentation script with detailed MCP integration

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inlceu this intot he poresation script

Replit-Commit-Author: Assistant
Replit-Commit-Session-Id: fb95cfda-0201-499a-811b-4d56364a96ec
Pavan Kumar 3 months ago
parent e1b59694d4
commit 32cf457aeb

@ -26,7 +26,40 @@ python examples/mcp_example/mock_multi_agent.py
- MCPServerSseParams for server connections
- Automatic task routing based on agent specialization
## 3. Demo Flow
## 3. MCP Integration Details
### Server Implementation:
```python
# 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:
```python
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:
```
@ -40,7 +73,7 @@ Enter a math problem: get price of AAPL
Enter a math problem: calculate moving average of [10,20,30,40,50] over 3 periods
```
## 4. Integration Highlights
## 5. Integration Highlights
1. Server Configuration:
- FastMCP initialization
@ -55,7 +88,12 @@ Enter a math problem: calculate moving average of [10,20,30,40,50] over 3 period
3. Communication Flow:
- Client request → Agent processing → MCP server → Response handling
## 5. Code Architecture
4. Error Handling:
- Graceful error management
- Automatic retry mechanisms
- Clear error reporting
## 6. Code Architecture
### Server Example (Math Server):
```python
@ -71,9 +109,35 @@ calculator = MathAgent("Calculator", "http://0.0.0.0:8000")
stock_analyst = MathAgent("StockAnalyst", "http://0.0.0.0:8001")
```
## 6. Key Benefits
## 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:
```python
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:
```python
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
```

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