feat(everything): add trigger-agentic-sampling tool

src/everything/docs/features.md

@@ -22,7 +22,9 @@
 - `trigger-long-running-operation` (tools/trigger-trigger-long-running-operation.ts): Simulates a multi-step operation over a given `duration` and number of `steps`; reports progress via `notifications/progress` when a `progressToken` is provided by the client.
 - `toggle-simulated-logging` (tools/toggle-simulated-logging.ts): Starts or stops simulated, random‑leveled logging for the invoking session. Respects the client’s selected minimum logging level.
 - `toggle-subscriber-updates` (tools/toggle-subscriber-updates.ts): Starts or stops simulated resource update notifications for URIs the invoking session has subscribed to.
-- `trigger-sampling-request` (tools/trigger-sampling-request.ts): Issues a `sampling/createMessage` request to the client/LLM using provided `prompt` and optional generation controls; returns the LLM’s response payload.
+- `trigger-sampling-request` (tools/trigger-sampling-request.ts): Issues a `sampling/createMessage` request to the client/LLM using provided `prompt` and optional generation controls; returns the LLM's response payload. Only registered if the client supports the `sampling` capability.
+- `trigger-agentic-sampling` (tools/trigger-agentic-sampling.ts): Demonstrates SEP-1577 sampling with tools. Sends a `prompt` to the LLM with tools available (`echo`, `add`), handles `tool_use` responses by executing tools locally, and loops until a final response or `maxIterations` is reached. Only registered if the client supports the `sampling.tools` capability.
+- `trigger-elicitation-request` (tools/trigger-elicitation-request.ts): Demonstrates user input elicitation by requesting a form with various field types (string, boolean, number, enum). Only registered if the client supports the `elicitation` capability.
 
 ## Prompts
 

src/everything/docs/structure.md

@@ -50,6 +50,7 @@ src/everything
      │   ├── gzip-file-as-resource.ts
      │   ├── toggle-simulated-logging.ts
      │   ├── toggle-subscriber-updates.ts
+     │   ├── trigger-agentic-sampling.ts
      │   ├── trigger-elicitation-request.ts
      │   ├── trigger-long-running-operation.ts
      │   └── trigger-sampling-request.ts
@@ -151,6 +152,8 @@ src/everything
   - Registers a `trigger-elicitation-request` tool that sends an `elicitation/create` request to the client/LLM and returns the elicitation result.
 - `trigger-sampling-request.ts`
   - Registers a `trigger-sampling-request` tool that sends a `sampling/createMessage` request to the client/LLM and returns the sampling result.
+- `trigger-agentic-sampling.ts`
+  - Registers a `trigger-agentic-sampling` tool that demonstrates SEP-1577 sampling with tools. Sends a prompt to the LLM with tools available (`echo`, `add`), handles `tool_use` responses by executing tools locally, and loops until a final response or max iterations is reached. Only registered if the client supports the `sampling.tools` capability.
 - `get-structured-content.ts`
   - Registers a `get-structured-content` tool that demonstrates structuredContent block responses.
 - `get-sum.ts`

src/everything/tools/index.ts

@@ -14,6 +14,7 @@ import { registerToggleSubscriberUpdatesTool } from "./toggle-subscriber-updates
 import { registerTriggerElicitationRequestTool } from "./trigger-elicitation-request.js";
 import { registerTriggerLongRunningOperationTool } from "./trigger-long-running-operation.js";
 import { registerTriggerSamplingRequestTool } from "./trigger-sampling-request.js";
+import { registerTriggerAgenticSamplingTool } from "./trigger-agentic-sampling.js";
 
 /**
  * Register the tools with the MCP server.
@@ -42,4 +43,5 @@ export const registerConditionalTools = (server: McpServer) => {
   registerGetRootsListTool(server);
   registerTriggerElicitationRequestTool(server);
   registerTriggerSamplingRequestTool(server);
+  registerTriggerAgenticSamplingTool(server);
 };

src/everything/tools/trigger-agentic-sampling.ts

@@ -0,0 +1,306 @@
+/**
+ * Agentic Sampling Tool - Demonstrates sampling with tools (MCP 2025-11-25)
+ *
+ * This tool sends a prompt to the client's LLM with tools available,
+ * handles tool_use responses, executes tools locally, and loops
+ * until a final text response is received.
+ *
+ * Flow:
+ * 1. Send sampling/createMessage with tools array
+ * 2. If stopReason="toolUse", execute tools and continue
+ * 3. Repeat until stopReason="endTurn" or iteration limit
+ */
+
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import {
+  CallToolResult,
+  CreateMessageRequest,
+  CreateMessageResultWithToolsSchema,
+  Tool,
+  ToolUseContent,
+  ToolResultContent,
+  SamplingMessage,
+  TextContent,
+} from "@modelcontextprotocol/sdk/types.js";
+import { z } from "zod";
+
+// ============================================================================
+// INPUT SCHEMA
+// ============================================================================
+
+const TriggerAgenticSamplingSchema = z.object({
+  prompt: z.string().describe("The prompt to send to the LLM"),
+  maxTokens: z
+    .number()
+    .default(1000)
+    .describe("Maximum tokens per response"),
+  maxIterations: z
+    .number()
+    .default(5)
+    .describe("Maximum tool loop iterations (safety limit)"),
+  availableTools: z
+    .array(z.string())
+    .default(["echo", "add"])
+    .describe("Names of server tools to make available to the LLM (default: echo, add)"),
+});
+
+// ============================================================================
+// TOOL DEFINITIONS
+// ============================================================================
+
+/**
+ * Tool definitions that we expose to the LLM during sampling.
+ * These mirror the actual server tools but are executed locally.
+ */
+const AVAILABLE_TOOL_DEFINITIONS: Record<string, Tool> = {
+  echo: {
+    name: "echo",
+    description: "Echoes back the input message",
+    inputSchema: {
+      type: "object",
+      properties: {
+        message: { type: "string", description: "Message to echo" },
+      },
+      required: ["message"],
+    },
+  },
+  add: {
+    name: "add",
+    description: "Adds two numbers together",
+    inputSchema: {
+      type: "object",
+      properties: {
+        a: { type: "number", description: "First number" },
+        b: { type: "number", description: "Second number" },
+      },
+      required: ["a", "b"],
+    },
+  },
+};
+
+// ============================================================================
+// LOCAL TOOL EXECUTION
+// ============================================================================
+
+/**
+ * Execute a tool locally and return the result.
+ * These implementations mirror the actual server tools.
+ */
+async function executeToolLocally(
+  toolName: string,
+  input: Record<string, unknown>
+): Promise<{ result: string; isError: boolean }> {
+  try {
+    switch (toolName) {
+      case "echo":
+        return { result: String(input.message), isError: false };
+
+      case "add": {
+        const a = Number(input.a);
+        const b = Number(input.b);
+        if (isNaN(a) || isNaN(b)) {
+          return { result: "Error: Both a and b must be numbers", isError: true };
+        }
+        return { result: String(a + b), isError: false };
+      }
+
+      default:
+        return { result: `Unknown tool: ${toolName}`, isError: true };
+    }
+  } catch (error) {
+    return {
+      result: `Error executing ${toolName}: ${error instanceof Error ? error.message : String(error)}`,
+      isError: true,
+    };
+  }
+}
+
+// ============================================================================
+// TOOL CONFIGURATION
+// ============================================================================
+
+const name = "trigger-agentic-sampling";
+const config = {
+  title: "Trigger Agentic Sampling Tool",
+  description:
+    "Demonstrates sampling with tools - sends a prompt to LLM with tools available, " +
+    "handles tool calls in a loop until final response. " +
+    "Requires client to support sampling.tools capability.",
+  inputSchema: TriggerAgenticSamplingSchema,
+};
+
+// ============================================================================
+// REGISTRATION
+// ============================================================================
+
+/**
+ * Registers the 'trigger-agentic-sampling' tool.
+ *
+ * Only registered if the client supports sampling.tools capability.
+ */
+export const registerTriggerAgenticSamplingTool = (server: McpServer) => {
+  // Check if client supports sampling with tools
+  const clientCapabilities = server.server.getClientCapabilities() || {};
+  const samplingCapability = clientCapabilities.sampling;
+
+  // Need sampling.tools capability
+  const clientSupportsSamplingWithTools =
+    samplingCapability !== undefined &&
+    typeof samplingCapability === "object" &&
+    samplingCapability !== null &&
+    "tools" in samplingCapability;
+
+  // If so, register tool
+  if (clientSupportsSamplingWithTools) {
+    server.registerTool(name, config, async (args, extra): Promise<CallToolResult> => {
+    const validatedArgs = TriggerAgenticSamplingSchema.parse(args);
+    const { prompt, maxTokens, maxIterations, availableTools } = validatedArgs;
+
+    // Build tools array from requested tool names
+    const tools: Tool[] = availableTools
+      .filter((name) => name in AVAILABLE_TOOL_DEFINITIONS)
+      .map((name) => AVAILABLE_TOOL_DEFINITIONS[name]);
+
+    if (tools.length === 0) {
+      return {
+        content: [
+          {
+            type: "text",
+            text: `Error: No valid tools specified. Available tools: ${Object.keys(AVAILABLE_TOOL_DEFINITIONS).join(", ")}`,
+          },
+        ],
+        isError: true,
+      };
+    }
+
+    console.error(
+      `[trigger-agentic-sampling] Starting with prompt: "${prompt.substring(0, 50)}..." ` +
+        `(${tools.length} tools, max ${maxIterations} iterations)`
+    );
+
+    // Initialize conversation
+    let messages: SamplingMessage[] = [
+      {
+        role: "user",
+        content: { type: "text", text: prompt },
+      },
+    ];
+
+    let iteration = 0;
+    let finalResponse = "";
+    const toolCallLog: string[] = [];
+
+    // Agentic loop
+    while (iteration < maxIterations) {
+      iteration++;
+      console.error(`[trigger-agentic-sampling] Iteration ${iteration}/${maxIterations}`);
+
+      // Build and send sampling request
+      // On last iteration, use toolChoice: none to force final response
+      const isLastIteration = iteration >= maxIterations;
+      const request: CreateMessageRequest = {
+        method: "sampling/createMessage",
+        params: {
+          messages,
+          tools,
+          toolChoice: isLastIteration ? { mode: "none" } : { mode: "auto" },
+          systemPrompt:
+            "You are a helpful assistant with access to tools. " +
+            "Use them when needed to answer questions accurately. " +
+            "When you have the final answer, respond with just the answer.",
+          maxTokens,
+          temperature: 0.7,
+        },
+      };
+
+      // Send the sampling request to the client
+      const result = await extra.sendRequest(request, CreateMessageResultWithToolsSchema);
+
+      console.error(`[trigger-agentic-sampling] Got response with stopReason: ${result.stopReason}`);
+
+      // Check if LLM wants to use tools
+      if (result.stopReason === "toolUse") {
+        // Extract tool_use blocks from content
+        const content = Array.isArray(result.content) ? result.content : [result.content];
+        const toolUseBlocks = content.filter(
+          (block): block is ToolUseContent => block.type === "tool_use"
+        );
+
+        if (toolUseBlocks.length === 0) {
+          console.error(
+            "[trigger-agentic-sampling] stopReason=toolUse but no tool_use blocks found"
+          );
+          finalResponse = "Error: Received toolUse stop reason but no tool_use blocks";
+          break;
+        }
+
+        // Add assistant message with tool_use to history
+        messages.push({
+          role: "assistant",
+          content: toolUseBlocks,
+        });
+
+        // Execute each tool and collect results
+        const toolResults: ToolResultContent[] = [];
+        for (const toolUse of toolUseBlocks) {
+          console.error(
+            `[trigger-agentic-sampling] Executing tool: ${toolUse.name}(${JSON.stringify(toolUse.input)})`
+          );
+
+          const execResult = await executeToolLocally(
+            toolUse.name,
+            toolUse.input as Record<string, unknown>
+          );
+
+          toolCallLog.push(
+            `${toolUse.name}(${JSON.stringify(toolUse.input)}) => ${execResult.result}`
+          );
+
+          toolResults.push({
+            type: "tool_result",
+            toolUseId: toolUse.id,
+            content: [{ type: "text", text: execResult.result } as TextContent],
+            isError: execResult.isError,
+          });
+        }
+
+        // Add user message with tool_results (MUST only contain tool_results per MCP spec)
+        messages.push({
+          role: "user",
+          content: toolResults,
+        });
+      } else {
+        // Final response (endTurn, maxTokens, stopSequence)
+        const content = Array.isArray(result.content) ? result.content : [result.content];
+        const textBlock = content.find((block) => block.type === "text");
+        finalResponse =
+          textBlock?.type === "text"
+            ? (textBlock as TextContent).text
+            : JSON.stringify(result.content);
+        console.error(
+          `[trigger-agentic-sampling] Final response received (stopReason: ${result.stopReason})`
+        );
+        break;
+      }
+    }
+
+    // Handle iteration limit reached
+    if (iteration >= maxIterations && !finalResponse) {
+      finalResponse = `[Reached maximum iterations (${maxIterations}) without final response]`;
+    }
+
+    // Build response with tool call log
+    let responseText = `Agentic sampling completed in ${iteration} iteration(s).\n`;
+
+    if (toolCallLog.length > 0) {
+      responseText += `\nTool calls:\n${toolCallLog.map((log) => `  - ${log}`).join("\n")}\n`;
+    }
+
+    responseText += `\nFinal response:\n${finalResponse}`;
+
+      return {
+        content: [{ type: "text", text: responseText }],
+      };
+    });
+  }
+};