From e1b59694d4c42ef3142e99aa35fdb308bfdc91bb Mon Sep 17 00:00:00 2001
From: Pavan Kumar <66913595+ascender1729@users.noreply.github.com>
Date: Fri, 18 Apr 2025 15:46:09 +0000
Subject: [PATCH] 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

---

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
---
 .replit                                     | 25 +++++++
 examples/mcp_example/mock_stock_server.py   |  2 +-
 examples/mcp_example/presentation_script.md | 79 +++++++++++++++++++++
 3 files changed, 105 insertions(+), 1 deletion(-)
 create mode 100644 examples/mcp_example/presentation_script.md

diff --git a/.replit b/.replit
index c9816a16..4ed1566a 100644
--- a/.replit
+++ b/.replit
@@ -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"
diff --git a/examples/mcp_example/mock_stock_server.py b/examples/mcp_example/mock_stock_server.py
index 3bbd6c76..6cf03946 100644
--- a/examples/mcp_example/mock_stock_server.py
+++ b/examples/mcp_example/mock_stock_server.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)
diff --git a/examples/mcp_example/presentation_script.md b/examples/mcp_example/presentation_script.md
new file mode 100644
index 00000000..98fd0e43
--- /dev/null
+++ b/examples/mcp_example/presentation_script.md
@@ -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