diff --git a/python/samples/04-hosting/a2a/README.md b/python/samples/04-hosting/a2a/README.md
index 0affc84e19..71cc9336c2 100644
--- a/python/samples/04-hosting/a2a/README.md
+++ b/python/samples/04-hosting/a2a/README.md
@@ -1,11 +1,12 @@
 # A2A Agent Examples
 
-This sample demonstrates how to host and consume agents using the [A2A (Agent2Agent) protocol](https://a2a-protocol.org/latest/) with the `agent_framework` package. There are two runnable entry points:
+This sample demonstrates how to host and consume agents using the [A2A (Agent2Agent) protocol](https://a2a-protocol.org/latest/) with the `agent_framework` package. There are three runnable entry points:
 
 | Run this file | To... |
 |---------------|-------|
 | **[`a2a_server.py`](a2a_server.py)** | Host an Agent Framework agent as an A2A-compliant server. |
 | **[`agent_with_a2a.py`](agent_with_a2a.py)** | Connect to an A2A server and send requests (non-streaming and streaming). |
+| **[`a2a_agent_as_function_tools.py`](a2a_agent_as_function_tools.py)** | Convert A2A agent skills into function tools for a host agent. |
 
 The remaining files are supporting modules used by the server:
 
@@ -27,6 +28,11 @@ Make sure to set the following environment variables before running the examples
 ### Required (Client)
 - `A2A_AGENT_HOST` — URL of the A2A server (e.g. `http://localhost:5001/`)
 
+### Required (Function Tools Sample)
+- `A2A_AGENT_HOST` — URL of the A2A server (e.g. `http://localhost:5000/`)
+- `AZURE_AI_PROJECT_ENDPOINT` — Your Azure AI Foundry project endpoint
+- `AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME` — Model deployment name (e.g. `gpt-4o`)
+
 ## Quick Start
 
 All commands below should be run from this directory:
@@ -55,3 +61,14 @@ In a separate terminal (from the same directory), point the client at a running
 $env:A2A_AGENT_HOST = "http://localhost:5001/"
 uv run python agent_with_a2a.py
 ```
+
+### 3. Run the Function Tools Sample
+
+This sample resolves the remote agent's skills and registers each one as a function tool
+on a host OpenAI-powered agent. The host agent then autonomously selects the right skill
+to handle the user's request.
+
+```powershell
+$env:A2A_AGENT_HOST = "http://localhost:5000/"
+uv run python a2a_agent_as_function_tools.py
+```
diff --git a/python/samples/04-hosting/a2a/a2a_agent_as_function_tools.py b/python/samples/04-hosting/a2a/a2a_agent_as_function_tools.py
new file mode 100644
index 0000000000..60d8317725
--- /dev/null
+++ b/python/samples/04-hosting/a2a/a2a_agent_as_function_tools.py
@@ -0,0 +1,152 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+import os
+import re
+
+import httpx
+from a2a.client import A2ACardResolver
+from agent_framework.a2a import A2AAgent
+from agent_framework.azure import AzureOpenAIResponsesClient
+from azure.identity import AzureCliCredential
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+"""
+A2A Agent Skills as Function Tools
+
+This sample demonstrates how to represent an A2A agent's skills as individual
+function tools and register them with a host agent. Each skill advertised in the
+remote agent's AgentCard becomes a separate tool that the host agent can invoke.
+
+Key concepts demonstrated:
+- Resolving an AgentCard from a remote A2A endpoint
+- Converting each skill into a FunctionTool via as_tool()
+- Registering those tools with a host agent
+- Having the host agent autonomously select and invoke A2A skills
+
+Prerequisites:
+- Set A2A_AGENT_HOST to the URL of a running A2A server
+- Set AZURE_AI_PROJECT_ENDPOINT to your Azure AI Foundry project endpoint
+- Set AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME to the model deployment name (e.g. gpt-4o)
+
+To run this sample:
+    cd python/samples/04-hosting/a2a
+    uv run python a2a_agent_as_function_tools.py
+"""
+
+
+async def main() -> None:
+    """Discover A2A agent skills and register them as tools on a host agent."""
+    # 1. Read environment configuration.
+    a2a_agent_host = os.getenv("A2A_AGENT_HOST")
+    if not a2a_agent_host:
+        raise ValueError("A2A_AGENT_HOST environment variable is not set")
+
+    project_endpoint = os.getenv("AZURE_AI_PROJECT_ENDPOINT")
+    deployment_name = os.getenv("AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME")
+    if not project_endpoint or not deployment_name:
+        raise ValueError(
+            "AZURE_AI_PROJECT_ENDPOINT and AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME must be set"
+        )
+
+    print(f"Connecting to A2A agent at: {a2a_agent_host}")
+
+    # 2. Resolve the remote agent card to discover its skills.
+    async with httpx.AsyncClient(timeout=60.0) as http_client:
+        resolver = A2ACardResolver(httpx_client=http_client, base_url=a2a_agent_host)
+        agent_card = await resolver.get_agent_card()
+
+    print(f"Found agent: {agent_card.name} ({len(agent_card.skills)} skill(s))")
+    for skill in agent_card.skills:
+        print(f"  - {skill.name}: {skill.description}")
+
+    # 3. Create the A2AAgent that wraps the remote endpoint.
+    async with A2AAgent(
+        name=agent_card.name,
+        description=agent_card.description,
+        agent_card=agent_card,
+        url=a2a_agent_host,
+    ) as a2a_agent:
+        # 4. Convert each A2A skill into a FunctionTool.
+        #    Skill names may contain spaces or special characters, so we
+        #    sanitize them into valid tool identifiers before passing to as_tool().
+        skill_tools = [
+            a2a_agent.as_tool(
+                name=re.sub(r"[^0-9A-Za-z]+", "_", skill.name),
+                description=skill.description or "",
+            )
+            for skill in agent_card.skills
+        ]
+
+        # 5. Create the host agent with the skill tools.
+        credential = AzureCliCredential()
+        client = AzureOpenAIResponsesClient(
+            project_endpoint=project_endpoint,
+            deployment_name=deployment_name,
+            credential=credential,
+        )
+        host_agent = client.as_agent(
+            name="assistant",
+            instructions="You are a helpful assistant. Use your tools to answer questions.",
+            tools=skill_tools,
+        )
+
+        # 6. Run the host agent — it will select and invoke the appropriate A2A skill tools.
+        query = "Show me all invoices for Contoso"
+        print(f"\nUser: {query}\n")
+        response = await host_agent.run(query)
+        print(f"Agent: {response}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
+
+
+"""
+Sample output:
+
+Connecting to A2A agent at: http://localhost:5000/
+Found agent: InvoiceAgent (1 skill(s))
+  - InvoiceQuery: Handles requests relating to invoices.
+
+User: Show me all invoices for Contoso
+
+Agent: Here are the invoices for Contoso:
+
+1. **Invoice ID:** INV789
+   - **Date:** 2026-02-15
+   - **Products:**
+     - T-Shirts: 150 units @ $10.00 = $1,500.00
+     - Hats: 200 units @ $15.00 = $3,000.00
+     - Glasses: 300 units @ $5.00 = $1,500.00
+   - **Total:** $6,000.00
+
+2. **Invoice ID:** INV333
+   - **Date:** 2026-03-14
+   - **Products:**
+     - T-Shirts: 400 units @ $11.00 = $4,400.00
+     - Hats: 600 units @ $15.00 = $9,000.00
+     - Glasses: 700 units @ $5.00 = $3,500.00
+   - **Total:** $16,900.00
+
+3. **Invoice ID:** INV666
+   - **Date:** 2026-02-06
+   - **Products:**
+     - T-Shirts: 2,500 units @ $8.00 = $20,000.00
+     - Hats: 1,200 units @ $10.00 = $12,000.00
+     - Glasses: 1,000 units @ $6.00 = $6,000.00
+   - **Total:** $38,000.00
+
+4. **Invoice ID:** INV999
+   - **Date:** 2026-03-19
+   - **Products:**
+     - T-Shirts: 1,400 units @ $10.50 = $14,700.00
+     - Hats: 1,100 units @ $9.00 = $9,900.00
+     - Glasses: 950 units @ $12.00 = $11,400.00
+   - **Total:** $36,000.00
+
+If you need more details or a specific invoice, please let me know!
+"""