How to integrate Serpapi MCP with LangChain

This guide walks you through connecting Serpapi to LangChain 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 LangChain 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 LangChain 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 LangChain 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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TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Serpapi project to Composio
  • Create a Tool Router MCP session for Serpapi
  • Initialize an MCP client and retrieve Serpapi tools
  • Build a LangChain agent that can interact with Serpapi
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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 step10 STEPS
1

Prerequisites

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming
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 dependencies

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • @composio/langchain provides Composio integration for LangChain
  • @langchain/mcp-adapters enables MCP client connections
  • @langchain/core is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models
5

Import dependencies

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv/config import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Serpapi functionality through MCP
6

Initialize Composio client

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Serpapi tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding
7

Create a Tool Router session

const session = await composio.create(
    userId as string,
    {
        toolkits: ['serpapi']
    }
);

const url = 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 session.mcp.url is the MCP server URL that your agent will use
  • This approach allows the agent to dynamically load and use Serpapi tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "serpapi-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Serpapi MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Serpapi tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model
9

Set up interactive chat interface

let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Serpapi related question or task to the agent.\n");

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

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;
    }

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

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
What's happening:
  • We initialize an empty conversationHistory list to maintain context across interactions
  • A readline interface is used to continuously accept user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the invoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully
10

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
What's happening:
  • We call the main() function to start the application

Complete Code

Here's the complete code to get you started with Serpapi and LangChain:

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['serpapi']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "serpapi-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Serpapi related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    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;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

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

Conclusion

You've successfully built a LangChain agent that can interact with Serpapi through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding 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

Use Serpapi MCP with OpenAI Agents SDK

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

Vercel AI SDK logo

Vercel AI SDK

Use Serpapi MCP with Vercel AI SDK

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. LangChain 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