genai-function-calling: Adds MCP example to openai-agents

genai-function-calling/openai-agents/Dockerfile

@@ -8,5 +8,6 @@ RUN --mount=type=cache,target=/root/.cache/pip pip install -r /tmp/requirements.
 RUN --mount=type=cache,target=/root/.cache/pip edot-bootstrap --action=install
 
 COPY main.py /
+COPY mcp_server.py /
 
-CMD [ "opentelemetry-instrument", "python", "main.py" ]
+ENTRYPOINT [ "opentelemetry-instrument", "python", "main.py" ]

genai-function-calling/openai-agents/README.md

@@ -52,6 +52,22 @@ Finally, run `main.py` (notice the prefix of `opentelemetry-instrument):
 dotenv run --no-override -- opentelemetry-instrument python main.py
 ```
 
+## Run with Model Context Protocol (MCP)
+
+[mcp_server](mcp_server.py) includes code needed to decouple tool discovery and invocation
+via the [Model Context Protocol (MCP) flow][flow-mcp]. To run using MCP, append
+`-- --mcp` flag to `dotenv run` or `docker compose run` command.
+
+For example, to run with Docker:
+```bash
+docker compose run --build --rm genai-function-calling --mcp
+```
+
+Or to run with Python:
+```bash
+dotenv run --no-override -- opentelemetry-instrument python main.py --mcp
+```
+
 ## Tests
 
 Tests use [pytest-vcr][pytest-vcr] to capture HTTP traffic for offline unit
@@ -88,3 +104,4 @@ OpenAI Agents SDK's OpenTelemetry instrumentation is via
 [pytest-vcr]: https://pytest-vcr.readthedocs.io/
 [test_main.yaml]: cassettes/test_main.yaml
 [openinference]:  https://github.com/Arize-ai/openinference/tree/main/python/instrumentation/openinference-instrumentation-openai-agents
+[flow-mcp]: ../README.md#model-context-protocol-flow

genai-function-calling/openai-agents/main.py

@@ -1,3 +1,4 @@
+import argparse
 import asyncio
 import os
 
@@ -19,7 +20,6 @@
 GLOBAL_TRACE_PROVIDER.shutdown()
 
 
-@function_tool(strict_mode=False)
 async def get_latest_elasticsearch_version(major_version: int = 0) -> str:
     """Returns the latest GA version of Elasticsearch in "X.Y.Z" format.
 
@@ -49,15 +49,15 @@ async def get_latest_elasticsearch_version(major_version: int = 0) -> str:
     return max(versions, key=lambda v: tuple(map(int, v.split("."))))
 
 
-async def main():
+async def run_agent(**agent_kwargs: dict):
     model_name = os.getenv("CHAT_MODEL", "gpt-4o-mini")
     openai_client = AsyncAzureOpenAI() if os.getenv("AZURE_OPENAI_API_KEY") else None
     model = OpenAIProvider(openai_client=openai_client, use_responses=False).get_model(model_name)
     agent = Agent(
         name="version_assistant",
-        tools=[get_latest_elasticsearch_version],
         model=model,
         model_settings=ModelSettings(temperature=0),
+        **agent_kwargs,
     )
 
     result = await Runner.run(
@@ -68,5 +68,30 @@ async def main():
     print(result.final_output)
 
 
+async def main():
+    parser = argparse.ArgumentParser(
+        prog="genai-function-calling",
+        description="Fetches the latest version of Elasticsearch 8",
+    )
+    parser.add_argument(
+        "--mcp",
+        action="store_true",
+        help="Run tools via a MCP server instead of directly",
+    )
+    args, _ = parser.parse_known_args()
+
+    if args.mcp:
+        from agents.mcp import MCPServerSse
+        from mcp_server import mcp_server
+
+        async with (
+            mcp_server([get_latest_elasticsearch_version]),
+            MCPServerSse(params={"url": "http://localhost:8000/sse"}) as mcp_client,
+        ):
+            await run_agent(mcp_servers=[mcp_client])
+    else:
+        await run_agent(tools=[function_tool(strict_mode=False)(get_latest_elasticsearch_version)])
+
+
 if __name__ == "__main__":
     asyncio.run(main())

genai-function-calling/openai-agents/mcp_server.py

@@ -0,0 +1,35 @@
+import asyncio
+import contextlib
+import httpx
+from mcp.server.fastmcp import FastMCP
+import uvicorn
+
+
+@contextlib.asynccontextmanager
+async def mcp_server(tools):
+    mcp_server = FastMCP(log_level="WARNING")
+    for tool in tools:
+        mcp_server.add_tool(tool)
+    # Manually setup uvicorn to allow shutting it down
+    config = uvicorn.Config(
+        mcp_server.sse_app(),
+        host="localhost",
+        port=8000,
+        log_level="critical",  # To suppress an SSE background task cancellation ERROR
+        timeout_graceful_shutdown=1,
+    )
+    server = uvicorn.Server(config)
+    server_task = asyncio.create_task(server.serve())
+    # Wait for the server to start
+    async with httpx.AsyncClient() as client:
+        while True:
+            try:
+                await client.get("http://localhost:8000/")
+                break
+            except httpx.ConnectError:
+                pass
+    try:
+        yield
+    finally:
+        server.should_exit = True
+        await server_task

genai-function-calling/openai-agents/requirements.txt

@@ -1,5 +1,6 @@
-openai-agents~=0.0.8
+openai-agents~=0.0.9
 httpx~=0.28.1
+mcp~=1.6.0
 
 elastic-opentelemetry~=1.0.0
 # Use openai-agents instrumentation from OpenInference