fix(mcp): improve MCP client response handling and display formatting

examples/mcp_example/mcp_client.py

@@ -0,0 +1,144 @@
+
+from swarms import Agent
+from swarms.tools.mcp_integration import MCPServerSseParams
+import asyncio
+import logging
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+class MCPClient:
+    def __init__(self):
+        # Configure MCP servers
+        self.math_server = MCPServerSseParams(
+            url="http://0.0.0.0:8000/mcp",
+            headers={"Content-Type": "application/json"},
+            timeout=5.0,
+            sse_read_timeout=30.0
+        )
+        
+        self.stock_server = MCPServerSseParams(
+            url="http://0.0.0.0:8001/mcp",
+            headers={"Content-Type": "application/json"},
+            timeout=5.0,
+            sse_read_timeout=30.0
+        )
+
+        # Initialize agents with specific servers
+        self.math_agent = Agent(
+            agent_name="Math Agent",
+            system_prompt="""You are a mathematical computation specialist with access to the following capabilities through the MCP server:
+            - Addition of two numbers
+            - Multiplication of two numbers  
+            - Power/exponent calculations
+            - Square root calculations
+            
+            Always follow these rules:
+            1. Only use tools that are available from the MCP server
+            2. First list the available tools when asked
+            3. Explain your mathematical approach before using tools
+            4. Provide clear step-by-step explanations of calculations""",
+            mcp_servers=[self.math_server],
+            max_loops=1,
+            streaming_on=True,
+            model_name="gpt-4o-mini",
+            temperature=0.1
+        )
+
+        self.stock_agent = Agent(
+            agent_name="Stock Agent",
+            system_prompt="""You are a stock market analysis specialist with access to the following capabilities through the MCP server:
+            - Get current stock prices
+            - Get trading volumes
+            - Calculate market capitalization
+            - Generate price statistics across multiple stocks
+            
+            Always follow these rules:
+            1. Only use tools that are available from the MCP server
+            2. First list the available tools when asked
+            3. Explain your analysis approach before using tools
+            4. Provide clear explanations of market metrics""",
+            mcp_servers=[self.stock_server],
+            max_loops=1,
+            streaming_on=True,
+            model_name="gpt-4o-mini",
+            temperature=0.1
+        )
+
+    async async def process_query(self, query: str):
+        try:
+            if query.lower() in ["capabilities", "what can you do", "what kind of problems you can solve"]:
+                return [
+                    {"agent": "Math Agent", "response": """I can help with mathematical computations including:
+- Addition of two numbers
+- Multiplication of two numbers
+- Power/exponent calculations  
+- Square root calculations"""},
+                    {"agent": "Stock Agent", "response": """I can help with stock market analysis including:
+- Get current stock prices
+- Get trading volumes
+- Calculate market capitalization
+- Generate price statistics across stocks"""}
+                ]
+            
+            # Run agents concurrently
+            results = await asyncio.gather(
+                self.math_agent.arun(query),
+                self.stock_agent.arun(query)
+            )
+            
+            # Format results
+            formatted_results = []
+            for idx, result in enumerate(results):
+                agent_name = "Math Agent" if idx == 0 else "Stock Agent"
+                if isinstance(result, dict):
+                    formatted_results.append({
+                        "agent": agent_name,
+                        "response": result.get("response", str(result))
+                    })
+                else:
+                    formatted_results.append({
+                        "agent": agent_name,
+                        "response": str(result)
+                    })
+            return formatted_results
+            
+        except Exception as e:
+            logger.error(f"Error processing query: {e}")
+            return None
+
+def main():
+    client = MCPClient()
+    
+    print("\nAvailable Agents and Capabilities:")
+    print("\nMath Agent:")
+    print("- Addition of two numbers")
+    print("- Multiplication of two numbers")
+    print("- Power/exponent calculations")
+    print("- Square root calculations")
+    
+    print("\nStock Agent:")
+    print("- Get current stock prices")
+    print("- Get trading volumes") 
+    print("- Calculate market capitalization")
+    print("- Generate price statistics")
+    
+    while True:
+        query = input("\nEnter your query (or 'exit' to quit): ")
+        if query.lower() == 'exit':
+            break
+            
+        results = asyncio.run(client.process_query(query))
+        
+        if results:
+            print("\nResults:")
+            for result in results:
+                if not result:
+                    continue
+                print(f"\n{result['agent']}:")
+                print("-" * 50)
+                print(result['response'])
+                print("-" * 50)
+
+if __name__ == "__main__":
+    main()