fix(mcp): implement proper client-side usage for MCP client integration

examples/mcp_example/mcp_client.py

@@ -1,144 +1,49 @@
-
 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 main():
-    def __init__(self):
+    # Configure MCP server connection 
-        # Configure MCP servers
+    math_server = MCPServerSseParams(
-        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(
+    # Initialize agent with MCP server
-            url="http://0.0.0.0:8001/mcp",
+    agent = Agent(
-            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:
+        agent_description="Agent for performing mathematical operations",
-            - Addition of two numbers
+        system_prompt="""You are a mathematical computation specialist. Use the available MCP server tools to:
-            - Multiplication of two numbers  
+        - Add numbers
-            - Power/exponent calculations
+        - Multiply numbers  
-            - Square root calculations
+        - Divide numbers
-            
+
-            Always follow these rules:
+        Always:
-            1. Only use tools that are available from the MCP server
+        1. Use only tools available from the MCP server
-            2. First list the available tools when asked
+        2. Explain your mathematical approach
-            3. Explain your mathematical approach before using tools
+        3. Show your work step by step""",
-            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,
+        mcp_servers=[math_server],
         streaming_on=True,
-            model_name="gpt-4o-mini",
+        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
+    print("\nMath Agent initialized with MCP capabilities")
-            formatted_results = []
+    print("Available operations:")
-            for idx, result in enumerate(results):
+    print("- Addition")
-                agent_name = "Math Agent" if idx == 0 else "Stock Agent"
+    print("- Multiplication") 
-                if isinstance(result, dict):
+    print("- Division")
-                    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): ")
+        query = input("\nEnter a math problem (or 'exit' to quit): ")
+
         if query.lower() == 'exit':
             break
 
-        results = asyncio.run(client.process_query(query))
+        # Process query through agent
-        
+        result = agent.run(query)
-        if results:
+        print("\nResult:", result)
-            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()