How to build MCP server that triggers an Agent using AI SDK

1. Set up your project mkdir code-reviewer cd code-reviewer npm init -y npm pkg set type=module 2. Install dependencies npm install @modelcontextprotocol/sdk npm install ai npm install @ai-sdk/openai 3. Create index.js import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js"; import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js"; import { z } from "zod"; // Contents of parallel-code-review.js is copied pasted from // https://sdk.vercel.ai/docs/foundations/agents#parallel-processing import { parallelCodeReview } from "./parallel-code-review.js"; const server = new McpServer({ name: "Code Reviewer", version: "1.0.0" }); server.tool("code_review", { code: z.string() }, async ({ code }) => { const { summary } = await parallelCodeReview(code); return { content: [{ type: "text", text: summary }], }; } ); const transport = new StdioServerTransport(); await server.connect(transport); The code in parallel-code-review.js is copied pasted from the example in https://sdk.vercel.ai/docs/foundations/agents#parallel-processing. // Source: https://sdk.vercel.ai/docs/foundations/agents#parallel-processing import { openai } from '@ai-sdk/openai'; import { generateText, generateObject } from 'ai'; import { z } from 'zod'; // Example: Parallel code review with multiple specialized reviewers export async function parallelCodeReview(code) { // ... } AI SDK defaults to looking at OPENAI_API_KEY which we will provide in next step. 4. Add to Cursor (or your MCP host of choice) { "mcpServers": { // other MCP servers... "Code Reviewer": { "command": "node", "args": [ "/absolute/path/to/your/code-reviewer/index.js" ], "env": { "OPENAI_API_KEY": "sk-proj-xxxxxxx" } } } } 5. Trigger your MCP by asking to use code reviewer

Apr 4, 2025 - 09:30

How to build MCP server that triggers an Agent using AI SDK

1. Set up your project

mkdir code-reviewer
cd code-reviewer
npm init -y
npm pkg set type=module

2. Install dependencies

npm install @modelcontextprotocol/sdk
npm install ai
npm install @ai-sdk/openai

3. Create index.js

import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";

// Contents of parallel-code-review.js is copied pasted from
// https://sdk.vercel.ai/docs/foundations/agents#parallel-processing
import { parallelCodeReview } from "./parallel-code-review.js";

const server = new McpServer({
  name: "Code Reviewer",
  version: "1.0.0"
});

server.tool("code_review",
  { code: z.string() },
  async ({ code }) => {
    const { summary } = await parallelCodeReview(code);
    return {
      content: [{ type: "text", text: summary }],
    };
  }
);

const transport = new StdioServerTransport();
await server.connect(transport);

The code in parallel-code-review.js is copied pasted from the example in https://sdk.vercel.ai/docs/foundations/agents#parallel-processing.

// Source: https://sdk.vercel.ai/docs/foundations/agents#parallel-processing
import { openai } from '@ai-sdk/openai';
import { generateText, generateObject } from 'ai';
import { z } from 'zod';

// Example: Parallel code review with multiple specialized reviewers
export async function parallelCodeReview(code) {
  // ...
}

AI SDK defaults to looking at OPENAI_API_KEY which we will provide in next step.

4. Add to Cursor (or your MCP host of choice)

{
  "mcpServers": {
    // other MCP servers...
    "Code Reviewer": {
      "command": "node",
      "args": [
        "/absolute/path/to/your/code-reviewer/index.js"
      ],
      "env": {
        "OPENAI_API_KEY": "sk-proj-xxxxxxx"
      }
    }
  }
}