MCP example for SSE

examples/mcp/filesystem_example/README.md

@@ -10,7 +10,7 @@ uv run python  python examples/mcp/filesystem_example/main.py
 
 ## Details
 
-The example uses the `MCPServerStdio` class from `agents`, with the command:
+The example uses the `MCPServerStdio` class from `agents.mcp`, with the command:
 
 ```bash
 npx -y "@modelcontextprotocol/server-filesystem" <samples_directory>

examples/mcp/git_example/README.md

@@ -10,16 +10,17 @@ uv run python examples/mcp/git_example/main.py
 
 ## Details
 
-The example uses the `MCPServerStdio` class from `agents`, with the command:
+The example uses the `MCPServerStdio` class from `agents.mcp`, with the command:
 
 ```bash
 uvx mcp-server-git
 ```
+
 Prior to running the agent, the user is prompted to provide a local directory path to their git repo. Using that, the Agent can invoke Git MCP tools like `git_log` to inspect the git commit log.
 
 Under the hood:
 
 1. The server is spun up in a subprocess, and exposes a bunch of tools like `git_log()`
 2. We add the server instance to the Agent via `mcp_agents`.
-3. Each time the agent runs, we call out to the MCP server to fetch the list of tools via `server.list_tools()`. The result is cached. 
+3. Each time the agent runs, we call out to the MCP server to fetch the list of tools via `server.list_tools()`. The result is cached.
 4. If the LLM chooses to use an MCP tool, we call the MCP server to run the tool via `server.run_tool()`.

examples/mcp/git_example/main.py

@@ -30,12 +30,8 @@ async def main():
     directory_path = input("Please enter the path to the git repository: ")
 
     async with MCPServerStdio(
-        params={
-            "command": "uvx",
-            "args": [
-                "mcp-server-git"
-            ]
-        }
+        cache_tools_list=True,  # Cache the tools list, for demonstration
+        params={"command": "uvx", "args": ["mcp-server-git"]},
     ) as server:
         with trace(workflow_name="MCP Git Example"):
             await run(server, directory_path)

examples/mcp/sse_example/README.md

@@ -0,0 +1,13 @@
+# MCP SSE Example
+
+This example uses a local SSE server in [server.py](server.py).
+
+Run the example via:
+
+```
+uv run python  python examples/mcp/sse_example/main.py
+```
+
+## Details
+
+The example uses the `MCPServerSse` class from `agents.mcp`. The server runs in a sub-process at `https://localhost:8000/sse`.

examples/mcp/sse_example/main.py

@@ -0,0 +1,83 @@
+import asyncio
+import os
+import shutil
+import subprocess
+import time
+from typing import Any
+
+from agents import Agent, Runner, gen_trace_id, trace
+from agents.mcp import MCPServer, MCPServerSse
+from agents.model_settings import ModelSettings
+
+
+async def run(mcp_server: MCPServer):
+    agent = Agent(
+        name="Assistant",
+        instructions="Use the tools to answer the questions.",
+        mcp_servers=[mcp_server],
+        model_settings=ModelSettings(tool_choice="required"),
+    )
+
+    # Use the `add` tool to add two numbers
+    message = "Add these numbers: 7 and 22."
+    print(f"Running: {message}")
+    result = await Runner.run(starting_agent=agent, input=message)
+    print(result.final_output)
+
+    # Run the `get_weather` tool
+    message = "What's the weather in Tokyo?"
+    print(f"\n\nRunning: {message}")
+    result = await Runner.run(starting_agent=agent, input=message)
+    print(result.final_output)
+
+    # Run the `get_secret_word` tool
+    message = "What's the secret word?"
+    print(f"\n\nRunning: {message}")
+    result = await Runner.run(starting_agent=agent, input=message)
+    print(result.final_output)
+
+
+async def main():
+    async with MCPServerSse(
+        name="SSE Python Server",
+        params={
+            "url": "http://localhost:8000/sse",
+        },
+    ) as server:
+        trace_id = gen_trace_id()
+        with trace(workflow_name="SSE Example", trace_id=trace_id):
+            print(f"View trace: https://platform.openai.com/traces/{trace_id}\n")
+            await run(server)
+
+
+if __name__ == "__main__":
+    # Let's make sure the user has uv installed
+    if not shutil.which("uv"):
+        raise RuntimeError(
+            "uv is not installed. Please install it: https://docs.astral.sh/uv/getting-started/installation/"
+        )
+
+    # We'll run the SSE server in a subprocess. Usually this would be a remote server, but for this
+    # demo, we'll run it locally at http://localhost:8000/sse
+    process: subprocess.Popen[Any] | None = None
+    try:
+        this_dir = os.path.dirname(os.path.abspath(__file__))
+        server_file = os.path.join(this_dir, "server.py")
+
+        print("Starting SSE server at http://localhost:8000/sse ...")
+
+        # Run `uv run server.py` to start the SSE server
+        process = subprocess.Popen(["uv", "run", server_file])
+        # Give it 3 seconds to start
+        time.sleep(3)
+
+        print("SSE server started. Running example...\n\n")
+    except Exception as e:
+        print(f"Error starting SSE server: {e}")
+        exit(1)
+
+    try:
+        asyncio.run(main())
+    finally:
+        if process:
+            process.terminate()

examples/mcp/sse_example/server.py

@@ -0,0 +1,33 @@
+import random
+
+import requests
+from mcp.server.fastmcp import FastMCP
+
+# Create server
+mcp = FastMCP("Echo Server")
+
+
+@mcp.tool()
+def add(a: int, b: int) -> int:
+    """Add two numbers"""
+    print(f"[debug-server] add({a}, {b})")
+    return a + b
+
+
+@mcp.tool()
+def get_secret_word() -> str:
+    print("[debug-server] get_secret_word()")
+    return random.choice(["apple", "banana", "cherry"])
+
+
+@mcp.tool()
+def get_current_weather(city: str) -> str:
+    print(f"[debug-server] get_current_weather({city})")
+
+    endpoint = "https://wttr.in"
+    response = requests.get(f"{endpoint}/{city}")
+    return response.text
+
+
+if __name__ == "__main__":
+    mcp.run(transport="sse")