Assistant checkpoint: Added presentation script and updated server configuration

Assistant generated file changes:
- examples/mcp_example/mock_stock_server.py: Fix FastMCP server configuration
- examples/mcp_example/presentation_script.md: Add presentation script
- .replit: Updated app configuration

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User prompt:

Give me updated presentation that how I could show that mcp integration has been done successfully into the ancient architecture and with examples of mock multi agent mock math server, mock stock server and how the local client side implementation and the server side implementation has been done I want to explain them the whole thing Give me a script step by step as a presentation

Replit-Commit-Author: Assistant
Replit-Commit-Session-Id: fb95cfda-0201-499a-811b-4d56364a96ec
Pavan Kumar 3 months ago
parent c4d674ae12
commit e1b59694d4

@ -74,3 +74,28 @@ mode = "sequential"
[[workflows.workflow.tasks]]
task = "shell.exec"
args = "python -m unittest tests/test_basic_example.py -v"
[[workflows.workflow]]
name = "Run MCP Demo"
author = 13983571
mode = "parallel"
[[workflows.workflow.tasks]]
task = "shell.exec"
args = "python examples/mcp_example/mock_stock_server.py &"
[[workflows.workflow.tasks]]
task = "shell.exec"
args = "sleep 2"
[[workflows.workflow.tasks]]
task = "shell.exec"
args = "python examples/mcp_example/mock_math_server.py &"
[[workflows.workflow.tasks]]
task = "shell.exec"
args = "sleep 2"
[[workflows.workflow.tasks]]
task = "shell.exec"
args = "python examples/mcp_example/mock_multi_agent.py"

@ -36,4 +36,4 @@ def calculate_moving_average(prices: list[float], window: int) -> Dict[str, Unio
if __name__ == "__main__":
print("Starting Mock Stock Server on port 8001...")
mcp.run(transport="sse", transport_kwargs={"host": "0.0.0.0", "port": 8001})
mcp.run(transport="sse", host="0.0.0.0", port=8001)

@ -0,0 +1,79 @@
# MCP Integration Demo Script
## 1. Setup & Architecture Overview
```bash
# 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. 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
```
## 4. 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
## 5. Code Architecture
### Server Example (Math Server):
```python
@mcp.tool()
def add(a: int, b: int) -> int:
"""Add two numbers together"""
return a + b
```
### Client Example (Multi-Agent):
```python
calculator = MathAgent("Calculator", "http://0.0.0.0:8000")
stock_analyst = MathAgent("StockAnalyst", "http://0.0.0.0:8001")
```
## 6. Key Benefits
1. Modular Architecture
2. Specialized Agents
3. Clean API Integration
4. Scalable Design
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