chore: import upstream snapshot with attribution

examples/snippets/servers/streamable_starlette_mount.py

@@ -0,0 +1,53 @@
+"""Run from the repository root:
+uvicorn examples.snippets.servers.streamable_starlette_mount:app --reload
+"""
+
+import contextlib
+
+from starlette.applications import Starlette
+from starlette.routing import Mount
+
+from mcp.server.mcpserver import MCPServer
+
+# Create the Echo server
+echo_mcp = MCPServer(name="EchoServer")
+
+
+@echo_mcp.tool()
+def echo(message: str) -> str:
+    """A simple echo tool"""
+    return f"Echo: {message}"
+
+
+# Create the Math server
+math_mcp = MCPServer(name="MathServer")
+
+
+@math_mcp.tool()
+def add_two(n: int) -> int:
+    """Tool to add two to the input"""
+    return n + 2
+
+
+# Create a combined lifespan to manage both session managers
+@contextlib.asynccontextmanager
+async def lifespan(app: Starlette):
+    async with contextlib.AsyncExitStack() as stack:
+        await stack.enter_async_context(echo_mcp.session_manager.run())
+        await stack.enter_async_context(math_mcp.session_manager.run())
+        yield
+
+
+# Create the Starlette app and mount the MCP servers
+app = Starlette(
+    routes=[
+        Mount("/echo", echo_mcp.streamable_http_app(stateless_http=True, json_response=True)),
+        Mount("/math", math_mcp.streamable_http_app(stateless_http=True, json_response=True)),
+    ],
+    lifespan=lifespan,
+)
+
+# Note: Clients connect to http://localhost:8000/echo/mcp and http://localhost:8000/math/mcp
+# To mount at the root of each path (e.g., /echo instead of /echo/mcp):
+# echo_mcp.streamable_http_app(streamable_http_path="/", stateless_http=True, json_response=True)
+# math_mcp.streamable_http_app(streamable_http_path="/", stateless_http=True, json_response=True)