MCP Server

npm install @modelcontextprotocol/sdk

import { Agent } from "jsr:@vibesjs/sdk";
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "npm:zod";
import { anthropic } from "npm:@ai-sdk/anthropic";

const model = anthropic("claude-opus-4-5");
const agent = new Agent({
  model,
  systemPrompt: "You are a helpful research assistant.",
});

// Create the MCP server
const server = new McpServer({
  name: "research-agent",
  version: "1.0.0",
});

// Register the agent as a tool
server.tool(
  "run_agent",
  "Ask the research agent a question and get a detailed answer.",
  {
    prompt: z.string().describe("The question or task for the agent"),
  },
  async ({ prompt }) => {
    const result = await agent.run(prompt);
    return {
      content: [{ type: "text", text: result.output }],
    };
  },
);

// Connect and run
const transport = new StdioServerTransport();
await server.connect(transport);

{
  "mcpServers": {
    "research-agent": {
      "command": "deno",
      "args": ["run", "--allow-all", "/path/to/your/server.ts"]
    }
  }
}

import { Agent } from "jsr:@vibesjs/sdk";
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StreamableHTTPServerTransport } from "@modelcontextprotocol/sdk/server/streamableHttp.js";
import { z } from "npm:zod";
import { anthropic } from "npm:@ai-sdk/anthropic";

const model = anthropic("claude-opus-4-5");
const agent = new Agent({
  model,
  systemPrompt: "You are a helpful research assistant.",
});

const server = new McpServer({
  name: "research-agent",
  version: "1.0.0",
});

server.tool(
  "run_agent",
  "Ask the research agent a question and get a detailed answer.",
  {
    prompt: z.string().describe("The question or task for the agent"),
  },
  async ({ prompt }) => {
    const result = await agent.run(prompt);
    return {
      content: [{ type: "text", text: result.output }],
    };
  },
);

// Serve over HTTP on port 8080
Deno.serve({ port: 8080 }, async (req) => {
  const transport = new StreamableHTTPServerTransport({ sessionIdHeader: "mcp-session-id" });
  await server.connect(transport);
  return transport.handleRequest(req);
});

import { MCPHttpClient, MCPToolset } from "jsr:@vibesjs/sdk";

const client = new MCPHttpClient({ url: "http://localhost:8080" });
await client.connect();
const toolset = new MCPToolset(client);
// Use toolset in another agent...

// Tool 1: quick answer
server.tool(
  "quick_answer",
  "Get a concise one-paragraph answer to a question.",
  { question: z.string() },
  async ({ question }) => {
    const result = await agent.run(`Answer briefly: ${question}`);
    return { content: [{ type: "text", text: result.output }] };
  },
);

// Tool 2: detailed analysis
server.tool(
  "analyze",
  "Get an in-depth analysis with supporting evidence.",
  {
    topic: z.string(),
    depth: z.enum(["surface", "deep"]).default("deep"),
  },
  async ({ topic, depth }) => {
    const prompt = depth === "deep"
      ? `Provide a detailed analysis of: ${topic}. Include examples and counterarguments.`
      : `Briefly analyze: ${topic}`;
    const result = await agent.run(prompt);
    return { content: [{ type: "text", text: result.output }] };
  },
);

const db = await openDatabase();

server.tool(
  "search_knowledge_base",
  "Search the internal knowledge base",
  { query: z.string() },
  async ({ query }) => {
    const result = await agent.run(query, { deps: { db } });
    return { content: [{ type: "text", text: result.output }] };
  },
);

// Clean up on process exit
globalThis.addEventListener("unload", async () => {
  await db.close();
});