diff --git a/examples/mcp/filesystem_example/README.md b/examples/mcp/filesystem_example/README.md
index 1b6b1837..83183fb4 100644
--- a/examples/mcp/filesystem_example/README.md
+++ b/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>
diff --git a/examples/mcp/git_example/README.md b/examples/mcp/git_example/README.md
index 35ff7cde..6a809afa 100644
--- a/examples/mcp/git_example/README.md
+++ b/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()`.
diff --git a/examples/mcp/git_example/main.py b/examples/mcp/git_example/main.py
index cfc15108..ab229e85 100644
--- a/examples/mcp/git_example/main.py
+++ b/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)
diff --git a/examples/mcp/sse_example/README.md b/examples/mcp/sse_example/README.md
new file mode 100644
index 00000000..605c2cc9
--- /dev/null
+++ b/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`.
diff --git a/examples/mcp/sse_example/main.py b/examples/mcp/sse_example/main.py
new file mode 100644
index 00000000..024b087e
--- /dev/null
+++ b/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()
diff --git a/examples/mcp/sse_example/server.py b/examples/mcp/sse_example/server.py
new file mode 100644
index 00000000..df364aa3
--- /dev/null
+++ b/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")