modelcontextprotocol
diff --git a/docs/sampling.md b/docs/sampling.md
@@ -0,0 +1,133 @@
+# Sampling
+
+Sampling lets a server ask the client to generate a message with an LLM. The
+SDK does not call a model provider by itself. Instead, the client opts in by
+registering a `sampling_callback`, and that callback decides which model or
+runtime to use.
+
+## Request Flow
+
+1. A server handler calls `ctx.session.create_message(...)`.
+2. The SDK sends a `sampling/createMessage` request to the connected client.
+3. The client's `sampling_callback` receives a `ClientRequestContext` and
+   `CreateMessageRequestParams`.
+4. The callback calls the model provider or local runtime that the client owns.
+5. The callback returns `CreateMessageResult` to the server.
+
+If the client does not register a sampling callback, sampling requests are
+answered with the SDK's default "Sampling not supported" error.
+
+## Register a Client Callback
+
+```python
+from mcp import ClientSession, types
+from mcp.client.context import ClientRequestContext
+
+
+async def handle_sampling_message(
+    context: ClientRequestContext,
+    params: types.CreateMessageRequestParams,
+) -> types.CreateMessageResult:
+    print(f"Sampling request {context.request_id}: {params.messages}")
+
+    return types.CreateMessageResult(
+        role="assistant",
+        content=types.TextContent(type="text", text="Hello from the client model"),
+        model="example-model",
+        stop_reason="endTurn",
+    )
+
+
+async def run(read_stream, write_stream):
+    async with ClientSession(read_stream, write_stream, sampling_callback=handle_sampling_message) as session:
+        await session.initialize()
+```
+
+The callback may return `types.ErrorData` instead of `CreateMessageResult` when
+the user rejects a request or the client cannot fulfill it.
+
+## Model Preferences
+
+`params.model_preferences` is advisory. The server can provide model name hints
+or priorities for cost, speed, and intelligence, but the client chooses how to
+interpret them.
+
+```python
+def pick_model(preferences: types.ModelPreferences | None) -> str:
+    if preferences and preferences.hints:
+        for hint in preferences.hints:
+            if hint.name in {"fast-model", "smart-model"}:
+                return hint.name
+
+    if preferences and (preferences.speed_priority or 0) > (preferences.intelligence_priority or 0):
+        return "fast-model"
+
+    return "smart-model"
+```
+
+Clients can ignore unsupported hints and should still apply their own policy,
+such as user approval, model availability, cost limits, or tenant configuration.
+
+## Context Fields
+
+`ClientRequestContext` is request metadata for the callback. It provides:
+
+- `context.session`: the client session handling the request.
+- `context.request_id`: the request id, when one is available.
+- `context.meta`: optional request metadata.
+
+It is not prompt context and does not automatically add resources or previous
+messages to the LLM request.
+
+`params.include_context` is the server's request for additional context. The SDK
+passes the value to the callback, but it does not attach context automatically.
+The client implementation decides what context it can safely include.
+
+When using `ClientSession` directly, a client that supports non-`none`
+`include_context` values can declare that with `sampling_capabilities`:
+
+```python
+session = ClientSession(
+    read_stream,
+    write_stream,
+    sampling_callback=handle_sampling_message,
+    sampling_capabilities=types.SamplingCapability(context=types.SamplingContextCapability()),
+)
+```
+
+```python
+async def handle_sampling_message(
+    context: ClientRequestContext,
+    params: types.CreateMessageRequestParams,
+) -> types.CreateMessageResult:
+    model = pick_model(params.model_preferences)
+    provider_messages = convert_sampling_messages(params.messages)
+
+    if params.system_prompt:
+        provider_messages.insert(0, {"role": "system", "content": params.system_prompt})
+
+    if params.include_context in {"thisServer", "allServers"}:
+        extra_context = await load_allowed_context(context, params.include_context)
+        provider_messages.insert(0, {"role": "system", "content": extra_context})
+
+    text = await call_your_llm(
+        model=model,
+        messages=provider_messages,
+        max_tokens=params.max_tokens,
+        temperature=params.temperature,
+        stop_sequences=params.stop_sequences,
+        metadata=params.metadata,
+    )
+
+    return types.CreateMessageResult(
+        role="assistant",
+        content=types.TextContent(type="text", text=text),
+        model=model,
+        stop_reason="endTurn",
+    )
+```
+
+In this example, `convert_sampling_messages`, `load_allowed_context`, and
+`call_your_llm` are application-specific helpers. Keeping them outside the SDK
+callback makes the example provider-neutral: the same callback shape works with
+a hosted model API, a local model runtime, or a test double.
diff --git a/mkdocs.yml b/mkdocs.yml
@@ -16,6 +16,7 @@ nav:
   - Migration Guide: migration.md
   - Documentation:
       - Concepts: concepts.md
+      - Sampling: sampling.md
       - Low-Level Server: low-level-server.md
       - Authorization: authorization.md
       - Testing: testing.md