diff --git a/ui/litellm-dashboard/src/components/mcp_tools/code-example.tsx b/ui/litellm-dashboard/src/components/mcp_tools/code-example.tsx
new file mode 100644
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+++ b/ui/litellm-dashboard/src/components/mcp_tools/code-example.tsx
@@ -0,0 +1,92 @@
+import React from 'react';
+
+const codeString = `import asyncio
+from openai import AsyncOpenAI
+from openai.types.chat import ChatCompletionUserMessageParam
+from mcp import ClientSession
+from mcp.client.sse import sse_client
+from litellm.experimental_mcp_client.tools import (
+    transform_mcp_tool_to_openai_tool,
+    transform_openai_tool_call_request_to_mcp_tool_call_request,
+)
+
+async def main():
+    # Initialize clients
+    client = AsyncOpenAI(
+        api_key="sk-1234", 
+        base_url="http://localhost:4000"
+    )
+    
+    # Connect to MCP
+    async with sse_client("http://localhost:4000/mcp/") as (read, write):
+        async with ClientSession(read, write) as session:
+            await session.initialize()
+            mcp_tools = await session.list_tools()
+            print("List of MCP tools for MCP server:", mcp_tools.tools)
+            
+            # Create message
+            messages = [
+                ChatCompletionUserMessageParam(
+                    content="Send an email about LiteLLM supporting MCP",
+                    role="user"
+                )
+            ]
+            
+            # Request with tools
+            response = await client.chat.completions.create(
+                model="gpt-4o",
+                messages=messages,
+                tools=[transform_mcp_tool_to_openai_tool(tool) for tool in mcp_tools.tools],
+                tool_choice="auto"
+            )
+            
+            # Handle tool call
+            if response.choices[0].message.tool_calls:
+                tool_call = response.choices[0].message.tool_calls[0]
+                if tool_call:
+                    # Convert format
+                    mcp_call = transform_openai_tool_call_request_to_mcp_tool_call_request(
+                        openai_tool=tool_call.model_dump()
+                    )
+                    
+                    # Execute tool
+                    result = await session.call_tool(
+                        name=mcp_call.name,
+                        arguments=mcp_call.arguments
+                    )
+                    
+                    print("Result:", result)
+
+# Run it
+asyncio.run(main())`;
+
+export const CodeExample: React.FC = () => {
+  return (
+    <div className="bg-white rounded-lg shadow h-full">
+      <div className="border-b px-4 py-3">
+        <h3 className="text-base font-medium text-gray-900">Using MCP Tools</h3>
+      </div>
+      <div className="p-4">
+        <div className="flex items-center gap-2 mb-2">
+          <div className="flex-1">
+            <div className="text-sm font-medium text-gray-700">Python integration</div>
+          </div>
+          <button 
+            className="text-xs bg-gray-100 hover:bg-gray-200 text-gray-600 px-2 py-1 rounded-md transition-colors"
+            onClick={() => {
+              navigator.clipboard.writeText(codeString);
+            }}
+          >
+            Copy
+          </button>
+        </div>
+        
+        <div className="overflow-auto rounded-md bg-gray-50 border" style={{ maxHeight: "calc(100vh - 280px)" }}>
+          <pre className="p-3 text-xs font-mono text-gray-800 whitespace-pre overflow-x-auto">
+            {codeString}
+          </pre>
+        </div>
+      </div>
+    </div>
+  );
+}; 
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