chore: import upstream snapshot with attribution

examples/stories/sampling/server_lowlevel.py

@@ -0,0 +1,45 @@
+"""Sampling primitive (lowlevel API): the same server→client round-trip, hand-built."""
+
+from typing import Any
+
+import mcp_types as types
+
+from mcp.server.context import ServerRequestContext
+from mcp.server.lowlevel import Server
+from stories._hosting import run_server_from_args
+
+
+def build_server() -> Server[Any]:
+    async def list_tools(
+        ctx: ServerRequestContext[Any], params: types.PaginatedRequestParams | None
+    ) -> types.ListToolsResult:
+        return types.ListToolsResult(
+            tools=[
+                types.Tool(
+                    name="summarize",
+                    description="Summarize text by asking the host's LLM via sampling/createMessage.",
+                    input_schema={
+                        "type": "object",
+                        "properties": {"text": {"type": "string"}},
+                        "required": ["text"],
+                    },
+                ),
+            ]
+        )
+
+    async def call_tool(ctx: ServerRequestContext[Any], params: types.CallToolRequestParams) -> types.CallToolResult:
+        assert params.name == "summarize"
+        assert params.arguments is not None
+        prompt = f"Summarize in one sentence:\n\n{params.arguments['text']}"
+        result = await ctx.session.create_message(  # pyright: ignore[reportDeprecated]
+            messages=[types.SamplingMessage(role="user", content=types.TextContent(text=prompt))],
+            max_tokens=200,
+        )
+        assert isinstance(result.content, types.TextContent)
+        return types.CallToolResult(content=[types.TextContent(text=result.content.text)])
+
+    return Server("sampling-example", on_list_tools=list_tools, on_call_tool=call_tool)
+
+
+if __name__ == "__main__":
+    run_server_from_args(build_server)