chore: import upstream snapshot with attribution

python/samples/demos/mcp_server/mcp_server_with_sampling.py

@@ -0,0 +1,116 @@
+# /// script # noqa: CPY001
+# dependencies = [
+#   "semantic-kernel[mcp]",
+# ]
+# ///
+# Copyright (c) Microsoft. All rights reserved.
+import logging
+from typing import Annotated, Any
+
+import anyio
+from mcp import types
+from mcp.server.lowlevel import Server
+from mcp.server.stdio import stdio_server
+
+from semantic_kernel import Kernel
+from semantic_kernel.functions import kernel_function
+from semantic_kernel.prompt_template import InputVariable, KernelPromptTemplate, PromptTemplateConfig
+
+logger = logging.getLogger(__name__)
+
+"""
+This sample demonstrates how to expose your Semantic Kernel `kernel` instance as a MCP server, with the a function 
+that uses sampling (see the docs: https://modelcontextprotocol.io/docs/concepts/sampling) to generate release notes.
+
+To run this sample, set up your MCP host (like Claude Desktop or VSCode Github Copilot Agents)
+with the following configuration:
+```json
+{
+    "mcpServers": {
+        "sk_release_notes": {
+            "command": "uv",
+            "args": [
+                "--directory=<path to sk project>/semantic-kernel/python/samples/demos/mcp_server",
+                "run",
+                "mcp_server_with_prompts.py"
+            ],
+        }
+    }
+}
+```
+
+Note: You might need to set the uv to it's full path.
+"""
+
+template = """{{$messages}}
+---
+Group the following PRs into one of these buckets for release notes, keeping the same order: 
+
+-New Features 
+-Enhancements and Improvements
+-Bug Fixes
+-Python Package Updates 
+
+Include the output in raw markdown.
+"""
+
+
+@kernel_function(
+    name="run_prompt",
+    description="This run the prompts for a full set of release notes based on the PR messages given.",
+)
+async def sampling_function(
+    messages: Annotated[str, "The list of PR messages, as a string with newlines"],
+    temperature: float = 0.0,
+    max_tokens: int = 1000,
+    # The include_in_function_choices is set to False, so it won't be included in the function choices,
+    # but it will get the server instance from the MCPPlugin that consumes this server.
+    server: Annotated[Server | None, "The server session", {"include_in_function_choices": False}] = None,
+) -> str:
+    if not server:
+        raise ValueError("Request context is required for sampling function.")
+    sampling_response = await server.request_context.session.create_message(
+        messages=[
+            types.SamplingMessage(role="user", content=types.TextContent(type="text", text=messages)),
+        ],
+        max_tokens=max_tokens,
+        temperature=temperature,
+        model_preferences=types.ModelPreferences(
+            hints=[types.ModelHint(name="gpt-4o-mini")],
+        ),
+    )
+    logger.info(f"Sampling response: {sampling_response}")
+    return sampling_response.content.text
+
+
+def run() -> None:
+    """Run the MCP server with the release notes prompt template."""
+    kernel = Kernel()
+    kernel.add_function("release_notes", sampling_function)
+    prompt = KernelPromptTemplate(
+        prompt_template_config=PromptTemplateConfig(
+            name="release_notes_prompt",
+            description="This creates the prompts for a full set of release notes based on the PR messages given.",
+            template=template,
+            input_variables=[
+                InputVariable(
+                    name="messages",
+                    description="These are the PR messages, they are a single string with new lines.",
+                    is_required=True,
+                    json_schema='{"type": "string"}',
+                )
+            ],
+        )
+    )
+
+    server = kernel.as_mcp_server(server_name="sk_release_notes", prompts=[prompt])
+
+    async def handle_stdin(stdin: Any | None = None, stdout: Any | None = None) -> None:
+        async with stdio_server() as (read_stream, write_stream):
+            await server.run(read_stream, write_stream, server.create_initialization_options())
+
+    anyio.run(handle_stdin)
+
+
+if __name__ == "__main__":
+    run()