diff --git a/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_local_mcp.py b/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_local_mcp.py
new file mode 100644
index 0000000000..8999fab566
--- /dev/null
+++ b/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_local_mcp.py
@@ -0,0 +1,64 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import os
+import asyncio
+
+from agent_framework import ChatAgent, MCPStreamableHTTPTool
+from agent_framework.azure import AzureOpenAIResponsesClient
+from azure.identity import AzureCliCredential
+
+"""
+Azure OpenAI Responses Client with local Model Context Protocol (MCP) Example
+
+This sample demonstrates integration of Azure OpenAI Responses Client with local Model Context Protocol (MCP)
+servers.
+"""
+
+
+# --- Below code uses Microsoft Learn MCP server over Streamable HTTP ---
+# --- Users can set these environment variables, or just edit the values below to their desired local MCP server
+MCP_NAME = os.environ.get("MCP_NAME", "Microsoft Learn MCP")  # example name
+MCP_URL = os.environ.get("MCP_URL", "https://learn.microsoft.com/api/mcp")   # example endpoint
+
+# Environment variables for Azure OpenAI Responses authentication
+# AZURE_OPENAI_ENDPOINT="<your-azure openai-endpoint>"
+# AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME="<your-deployment-name>"
+# AZURE_OPENAI_API_VERSION="<your-api-version>"  # e.g. "2025-03-01-preview"
+
+async def main():
+    """Example showing local MCP tools for a Azure OpenAI Responses Agent."""
+    # AuthN: use Azure CLI
+    credential = AzureCliCredential()
+
+    # Build an agent backed by Azure OpenAI Responses
+    # (endpoint/deployment/api_version can also come from env vars above)
+    responses_client = AzureOpenAIResponsesClient(
+        credential=credential,
+    )
+
+    agent: ChatAgent = responses_client.create_agent(
+        name="DocsAgent",
+        instructions=(
+            "You are a helpful assistant that can help with Microsoft documentation questions."
+        ),
+    )
+
+    # Connect to the MCP server (Streamable HTTP)
+    async with MCPStreamableHTTPTool(
+        name=MCP_NAME,
+        url=MCP_URL,
+        
+    ) as mcp_tool:
+        # First query — expect the agent to use the MCP tool if it helps
+        q1 = "How to create an Azure storage account using az cli?"
+        r1 = await agent.run(q1, tools=mcp_tool)
+        print("\n=== Answer 1 ===\n", r1.text)
+
+        # Follow-up query (connection is reused)
+        q2 = "What is Microsoft Agent Framework?"
+        r2 = await agent.run(q2, tools=mcp_tool)
+        print("\n=== Answer 2 ===\n", r2.text)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())