How to integrate Serpapi MCP with Vercel AI SDK v6

This guide walks you through connecting Serpapi to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Serpapi agent that can find latest job postings for python developers, show recent stock news for apple inc, list concerts happening in new york this week through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Serpapi account through Composio's Serpapi MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Introduction

This guide walks you through connecting Serpapi to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Serpapi agent that can find latest job postings for python developers, show recent stock news for apple inc, list concerts happening in new york this week through natural language commands.

This guide will help you understand how to give your Vercel AI SDK agent real control over a Serpapi account through Composio's Serpapi MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Serpapi with

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TL;DR

Here's what you'll learn:
  • How to set up and configure a Vercel AI SDK agent with Serpapi integration
  • Using Composio's Tool Router to dynamically load and access Serpapi tools
  • Creating an MCP client connection using HTTP transport
  • Building an interactive CLI chat interface with conversation history management
  • Handling tool calls and results within the Vercel AI SDK framework

What is Vercel AI SDK?

The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state.

Key features include:

  • streamText: Core function for streaming responses with real-time tool support
  • MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp
  • Step Counting: Control multi-step tool execution with stopWhen: stepCountIs()
  • OpenAI Provider: Native integration with OpenAI models

What is the Serpapi MCP server, and what's possible with it?

The Serpapi MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your SerpApi account. It provides structured and secure access to real-time search engine results, so your agent can perform actions like scraping search data, analyzing trends, retrieving product listings, and exploring local business information on your behalf.

  • Real-time web search across engines: Instantly fetch structured search results from Google, Bing, Baidu, and DuckDuckGo for any query, including organic results, ads, and rich snippets.
  • Product and marketplace data extraction: Automatically search eBay for products and retrieve detailed, structured product data to power research or price comparison workflows.
  • Event and job listings discovery: Let your agent search Google Events and Google Jobs to uncover upcoming events, conferences, or relevant job postings with granular location and keyword filters.
  • Financial and stock information retrieval: Seamlessly pull the latest company details, stock prices, market news, and trends from Google Finance using a simple query.
  • Location and map-based search: Enable your agent to perform Google Maps searches to find local businesses, attractions, or venues—complete with structured location data and optional GPS-based results.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS
1

Prerequisites

Before you begin, make sure you have:
  • Node.js and npm installed
  • A Composio account with API key
  • An OpenAI API key
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install required dependencies

bash
npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv

First, install the necessary packages for your project.

What you're installing:

  • @ai-sdk/openai: Vercel AI SDK's OpenAI provider
  • @ai-sdk/mcp: MCP client for Vercel AI SDK
  • @composio/core: Composio SDK for tool integration
  • ai: Core Vercel AI SDK
  • dotenv: Environment variable management
4

Set up environment variables

bash
OPENAI_API_KEY=your_openai_api_key_here
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here

Create a .env file in your project root.

What's needed:

  • OPENAI_API_KEY: Your OpenAI API key for GPT model access
  • COMPOSIO_API_KEY: Your Composio API key for tool access
  • COMPOSIO_USER_ID: A unique identifier for the user session
5

Import required modules and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey,
});
What's happening:
  • We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio
  • The dotenv/config import automatically loads environment variables
  • The MCP client import enables connection to Composio's tool server
6

Create Tool Router session and initialize MCP client

typescript
async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["serpapi"],
  });

  const mcpUrl = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Serpapi tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned mcp object contains the URL and authentication headers needed to connect to the MCP server
  • This session provides access to all Serpapi-related tools through the MCP protocol
7

Connect to MCP server and retrieve tools

typescript
const mcpClient = await createMCPClient({
  transport: {
    type: "http",
    url: mcpUrl,
    headers: session.mcp.headers, // Authentication headers for the Composio MCP server
  },
});

const tools = await mcpClient.tools();
What's happening:
  • We're creating an MCP client that connects to our Composio Tool Router session via HTTP
  • The mcp.url provides the endpoint, and mcp.headers contains authentication credentials
  • The type: "http" is important - Composio requires HTTP transport
  • tools() retrieves all available Serpapi tools that the agent can use
8

Initialize conversation and CLI interface

typescript
let messages: ModelMessage[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log(
  "Ask any questions related to serpapi, like summarize my last 5 emails, send an email, etc... :)))\n",
);

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();
What's happening:
  • We initialize an empty messages array to maintain conversation history
  • A readline interface is created to accept user input from the command line
  • Instructions are displayed to guide the user on how to interact with the agent
9

Handle user input and stream responses with real-time tool feedback

typescript
rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({ role: "user", content: trimmedInput });
  console.log("\nAgent is thinking...\n");

  try {
    const stream = streamText({
      model: openai("gpt-5"),
      messages,
      tools,
      toolChoice: "auto",
      stopWhen: stepCountIs(10),
      onStepFinish: (step) => {
        for (const toolCall of step.toolCalls) {
          console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

  rl.on("close", async () => {
    await mcpClient.close();
    console.log("\n👋 Session ended.");
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • We use streamText instead of generateText to stream responses in real-time
  • toolChoice: "auto" allows the model to decide when to use Serpapi tools
  • stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations
  • onStepFinish callback displays which tools are being used in real-time
  • We iterate through the text stream to create a typewriter effect as the agent responds
  • The complete response is added to conversation history to maintain context
  • Errors are caught and displayed with helpful retry suggestions

Complete Code

Here's the complete code to get you started with Serpapi and Vercel AI SDK:

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey,
});

async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["serpapi"],
  });

  const mcpUrl = session.mcp.url;

  const mcpClient = await createMCPClient({
    transport: {
      type: "http",
      url: mcpUrl,
      headers: session.mcp.headers, // Authentication headers for the Composio MCP server
    },
  });

  const tools = await mcpClient.tools();

  let messages: ModelMessage[] = [];

  console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
  console.log(
    "Ask any questions related to serpapi, like summarize my last 5 emails, send an email, etc... :)))\n",
  );

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
      console.log("\nGoodbye!");
      rl.close();
      process.exit(0);
    }

    if (!trimmedInput) {
      rl.prompt();
      return;
    }

    messages.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    try {
      const stream = streamText({
        model: openai("gpt-5"),
        messages,
        tools,
        toolChoice: "auto",
        stopWhen: stepCountIs(10),
        onStepFinish: (step) => {
          for (const toolCall of step.toolCalls) {
            console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

  rl.on("close", async () => {
    await mcpClient.close();
    console.log("\n👋 Session ended.");
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});

Conclusion

You've successfully built a Serpapi agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback.

Key features of this implementation:

  • Real-time streaming responses for a better user experience with typewriter effect
  • Live tool execution feedback showing which tools are being used as the agent works
  • Dynamic tool loading through Composio's Tool Router with secure authentication
  • Multi-step tool execution with configurable step limits (up to 10 steps)
  • Comprehensive error handling for robust agent execution
  • Conversation history maintenance for context-aware responses

You can extend this further by adding custom error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.
TOOLS

Supported Tools

Every Serpapi action and event your agent gets out of the box.

Search Baidu with Query

Search Baidu (Chinese search engine) and retrieve search results.

Bing Maps Search

Tool to scrape Bing Maps results using SerpApi.

Bing Search

Retrieve Bing Search Engine Results via SerpAPI (requires active SerpAPI connection; if unavailable, use COMPOSIO_SEARCH_WEB or COMPOSIO_SEARCH_NEWS).

DuckDuckGo Light Search

Tool to access the world's fastest DuckDuckGo Search API via SerpApi.

DuckDuckGo Maps search

Scrapes DuckDuckGo Maps results via SerpApi.

DuckDuckGo search

Performs a DuckDuckGo search via SerpApi to retrieve SERP data, including organic results, ads, and structured information.

eBay Search

Retrieve eBay Search Results via SerpApi (requires active SerpApi connected account).

Search Google Events

Searches for events (e.

Search finance

Retrieves structured financial information (e.

Get Location Options

Tool to get available location options for Google searches.

Get Facebook profile information

Tool to retrieve public information from a Facebook profile or page using SerpAPI.

Get Google About This Result

Tool to get Google 'About this result' information for a website.

Get Google Hotels Autocomplete

Tool to get autocomplete suggestions for Google Hotels destination searches.

Get Google Images Related Content

Get related content for a specific Google Images result.

Get Google Patent Details

Tool to retrieve detailed information about a specific patent or scholar document from Google Patents via SerpApi.

Get Search Archive

Tool to retrieve results from a previous async search using its search ID.

Google Domains List

Retrieve the list of supported Google domains for search queries.

Google Forums Search

Tool to scrape forum results from Google's Forums Platform using SerpApi.

Google Jobs Search

Retrieve Google Jobs Search Results via SerpApi.

Google Lens search

Performs reverse image search using Google Lens to find visually similar images, products, and related content.

Google Light Search

Retrieve Google Light Search Results via SerpApi.

Google Maps Posts

Scrapes Google Maps Posts for a business location via SerpApi.

Google maps search

Performs a Google Maps search via SERP API.

Google Play Product Search

Tool to retrieve detailed Google Play product information using SerpApi.

Google Scholar Author Profile

Scrapes full Google Scholar Author page including articles, citations, metrics, and co-authors.

Google Scholar Cite

Scrapes full Google Scholar Citations with multiple citation formats.

Google Videos Light Search

Tool to scrape Google Videos results using SerpApi's ultra-fast Google Videos Light API.

Hotel Search

Retrieve Google Hotel Search Results.

Image search

Searches Google Images via SERP API for a given query, returning structured image results.

Naver Search

Tool to search Naver (South Korea's leading search engine) for Korean web results and content.

Search for news articles

Searches Google News (via SerpApi, `tbm=nws`) for articles matching a query; precise key-phrase queries yield best results.

OpenTable Reviews Search

Tool to scrape OpenTable restaurant reviews using SerpApi.

Google Play Search

Retrieve Google Play Store Search Results.

Search Google Scholar

Searches Google Scholar via SerpApi for academic literature, papers, articles, and citations based on a query.

Serp API search

Performs a real-time Google search via the SerpAPI connection (must be active; if unavailable, use COMPOSIO_SEARCH_WEB or other COMPOSIO_SEARCH_* tools).

Search Apple App Store

Tool to search Apple App Store for iOS and Mac apps.

Google Images Light Search

Tool to scrape Google Images results using SerpApi's Google Images Light API.

Search Google Local Services

Search Google Local Services for service providers like electricians, plumbers, HVAC technicians, and more.

Search Yelp businesses

Tool to search Yelp for businesses and places using SerpApi.

Shopping search

Searches Google Shopping via SerpAPI for a specific product, returning structured listings in results.

Google Trends search

Fetches Google Trends data; returns relative 0–100 interest indices (not absolute volumes) meaningful only when comparing queries within the same request.

Walmart Product Reviews

Tool to scrape full Walmart product reviews using SerpApi's Walmart Product Reviews API.

Walmart Search

Retrieve Walmart Search Results.

Yahoo Search

Retrieve Yahoo!

Yahoo Videos Search

Scrape Yahoo!

Yandex Images Search

Tool to search Yandex Images for image results with advanced filters.

Yandex Search

Retrieve Yandex Search Results.

YouTube Search

Retrieve YouTube Search Results.

FRAMEWORKS

How to build Serpapi MCP Agent with another framework

ChatGPT logo

ChatGPT

Use Serpapi MCP with ChatGPT

OpenAI Agents SDK logo

OpenAI Agents SDK

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Claude Agent SDK logo

Claude Agent SDK

Use Serpapi MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Serpapi MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Serpapi MCP with Claude Cowork

Codex logo

Codex

Use Serpapi MCP with Codex

Cursor logo

Cursor

Use Serpapi MCP with Cursor

OpenClaw logo

OpenClaw

Use Serpapi MCP with OpenClaw

Hermes logo

Hermes

Use Serpapi MCP with Hermes

CLI logo

CLI

Use Serpapi MCP with CLI

Google ADK logo

Google ADK

Use Serpapi MCP with Google ADK

LangChain logo

LangChain

Use Serpapi MCP with LangChain

Mastra AI logo

Mastra AI

Use Serpapi MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Serpapi MCP with LlamaIndex

CrewAI logo

CrewAI

Use Serpapi MCP with CrewAI

OpenCode logo

OpenCode

Use Serpapi MCP with OpenCode

VS Code logo

VS Code

Use Serpapi MCP with VS Code

FAQ

Frequently asked questions

With a standalone Serpapi MCP server, the agents and LLMs can only access a fixed set of Serpapi tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Serpapi and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Vercel AI SDK v6 fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Serpapi tools.

Yes, absolutely. You can configure which Serpapi scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Serpapi data and credentials are handled as safely as possible.

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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati
Harsha Gaddipati
Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya
Abhi Arya
Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave
Nirman Dave
CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu
Ryan Yu
Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola
Tomisin Jenrola
Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche
Jerome Leclanche
Co-Founder, Ingram Technologies