# How to integrate Serphouse MCP with LangChain

```json
{
  "title": "How to integrate Serphouse MCP with LangChain",
  "toolkit": "Serphouse",
  "toolkit_slug": "serphouse",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/serphouse/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/serphouse/framework/langchain.md",
  "updated_at": "2026-03-29T06:49:50.974Z"
}
```

## Introduction

This guide walks you through connecting Serphouse to LangChain using the Composio tool router. By the end, you'll have a working Serphouse agent that can get serp results for 'ai marketing tools', list top keywords for competitor domain, summarize ranking changes for your site through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Serphouse account through Composio's Serphouse MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Serphouse with

- [OpenAI Agents SDK](https://composio.dev/toolkits/serphouse/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/serphouse/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/serphouse/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/serphouse/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/serphouse/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/serphouse/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/serphouse/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/serphouse/framework/cli)
- [Google ADK](https://composio.dev/toolkits/serphouse/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/serphouse/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/serphouse/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/serphouse/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/serphouse/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Connect your Serphouse project to Composio
- Create a Tool Router MCP session for Serphouse
- Initialize an MCP client and retrieve Serphouse tools
- Build a LangChain agent that can interact with Serphouse
- 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 Serphouse MCP server, and what's possible with it?

The Serphouse MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Serphouse account. It provides structured and secure access so your agent can perform Serphouse operations on your behalf.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `SERPHOUSE_ACCOUNT_INFO` | Get Account Information | Tool to retrieve account information including active plan, credit usage, and account details. Use when you need to check account status, remaining credits, or active subscription plans. |
| `SERPHOUSE_DOMAIN_LIST` | Get Domain List | Tool to retrieve comprehensive list of search engine domains supported by the SERP API including Google, Bing, and Yahoo. Use when you need to know which domains are available for search queries. |
| `SERPHOUSE_GOOGLE_JOBS_SEARCH` | Google Jobs Search | Tool to perform real-time Google Jobs search to retrieve job listings. Use when you need to search for job postings on Google with specific query terms, location, and filters. |
| `SERPHOUSE_GOOGLE_SERP_ADVANCED_SCHEDULED` | Schedule Google SERP Advanced Search | Tool to schedule Google SERP scraping tasks that fetch up to 100 results by iterating through multiple result pages. Use when you need comprehensive search results beyond Google's 10-result limit. Credits are reserved upfront based on max_pages (1 page = 1 credit), with automatic refunds for unused pages. |
| `SERPHOUSE_GET_LANGUAGE_LIST` | Get Language List | Tool to retrieve full list of languages supported by Google, Bing, and Yahoo for SERP requests. Use when you need language codes for making SERP API requests or when configuring language-specific searches. |
| `SERPHOUSE_SEARCH_LOCATIONS` | Search Locations | Tool to search and retrieve available locations for SERP API from Google or Bing geographical targeting data. Use when you need to find valid location targets before making SERP API requests. |
| `SERPHOUSE_CHECK_SERP_TASK_STATUS` | Check SERP Task Status | Tool to check the status of a previously submitted SERP task. Use when monitoring task completion progress or verifying whether a SERP task has finished processing. |
| `SERPHOUSE_SERP_LIVE_SEARCH_GET` | SERP Live Search (GET) | Tool to execute real-time search requests and retrieve search engine results immediately via HTTP GET. Use when you need to perform searches on Google, Bing, or Yahoo and get instant SERP data. |
| `SERPHOUSE_EXECUTE_SERP_LIVE_POST_SEARCH` | Execute SERP Live POST Search | Tool to execute real-time search requests and retrieve search engine results immediately using HTTP POST method. Use when you need to get fresh SERP data from Google, Bing, or Yahoo with specific location and device targeting. Supports web, news, image, and shopping search types with advanced filtering options. |
| `SERPHOUSE_SCHEDULE_SERP_TASKS` | Schedule SERP Tasks | Tool to schedule SERP search tasks for asynchronous processing. Use when you need to queue multiple search tasks (up to 100 at once) for later execution. Results can be retrieved via webhook or polling. |
| `SERPHOUSE_GET_TRENDS_CATEGORIES_LIST` | Get Trends Categories List | Tool to retrieve the full list of categories and subcategories for Google Trends searches. Use when you need category IDs for filtering trends analysis. |
| `SERPHOUSE_CHECK_TREND_SEARCH_STATUS` | Check Trend Search Status | Tool to check the status of a previously submitted trend search task. Use when you need to monitor completion progress of a trend search. |
| `SERPHOUSE_GET_TRENDS_COUNTRY_LIST` | Get Trends Country List | Tool to retrieve the full list of countries and states for Google Trends searches. Use when you need geographic targeting options for trends analysis. |
| `SERPHOUSE_GET_TREND_SEARCH_RESULTS` | Get Trend Search Results | Tool to retrieve the results of a completed trend search query. Use when you need to fetch trend data for a specific task ID that was previously submitted. The task must be completed before results are available. |
| `SERPHOUSE_GET_TRENDS_LANGUAGE_LIST` | Get Trends Language List | Tool to retrieve the full list of supported languages for Google Trends searches. Use when you need to identify valid language codes for trend search requests. |
| `SERPHOUSE_SCHEDULE_GOOGLE_TRENDS_SEARCH` | Schedule Google Trends Search | Tool to schedule Google Trends search tasks with configuration for keywords, time ranges, and geographic locations. Use when you need to collect Google Trends data for specific keywords, time periods, or regions. Supports batch processing of up to 100 tasks. |
| `SERPHOUSE_PERFORM_GOOGLE_TRENDS_SEARCH` | Perform Google Trends Search | Tool to perform real-time Google Trends search to retrieve trend data for specified keywords. Use when you need to analyze keyword popularity across time periods and geographic locations. |
| `SERPHOUSE_GET_TRENDS_TIMEZONE_LIST` | Get Trends Timezone List | Tool to retrieve full list of timezones and offset values for use in Google Trend search requests. Use when you need timezone information for trend analysis or when configuring timezone-specific trend searches. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Serphouse MCP server is an implementation of the Model Context Protocol that connects your AI agent to Serphouse. It provides structured and secure access so your agent can perform Serphouse operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

No description provided.

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

No description provided.
```python
pip install composio-langchain langchain-mcp-adapters langchain python-dotenv
```

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

### 3. Set up environment variables

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
```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
```

### 4. Import dependencies

No description provided.
```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
```

```typescript
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();
```

### 5. Initialize Composio client

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 Serphouse tools
- Validating that COMPOSIO_USER_ID is also set before proceeding
```python
async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
```

```typescript
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()
    });
```

### 6. Create a Tool Router session

What's happening:
- We're creating a Tool Router session that gives your agent access to Serphouse 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 Serphouse tools as needed
```python
# Create Tool Router session for Serphouse
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['serphouse']
)

url = session.mcp.url
```

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

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "serphouse-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
```

```typescript
const client = new MultiServerMCPClient({
    "serphouse-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 });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

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

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
```

```typescript
let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Serphouse 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);
    });
```

### 9. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(main())
```

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

## Complete Code

```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['serphouse']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "serphouse-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Serphouse related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
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: ['serphouse']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "serphouse-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 Serphouse 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 Serphouse 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.

## How to build Serphouse MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/serphouse/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/serphouse/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/serphouse/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/serphouse/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/serphouse/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/serphouse/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/serphouse/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/serphouse/framework/cli)
- [Google ADK](https://composio.dev/toolkits/serphouse/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/serphouse/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/serphouse/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/serphouse/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/serphouse/framework/crew-ai)

## Related Toolkits

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- [Tavily](https://composio.dev/toolkits/tavily) - Tavily offers powerful search and data retrieval from documents, databases, and the web. It helps teams locate and filter information instantly, saving hours on research.
- [Exa](https://composio.dev/toolkits/exa) - Exa is a data extraction and search platform for gathering and analyzing information from websites, APIs, or databases. It helps teams quickly surface insights and automate data-driven workflows.
- [Serpapi](https://composio.dev/toolkits/serpapi) - SerpApi is a real-time API for structured search engine results. It lets you automate SERP data collection, parsing, and analysis for SEO and research.
- [Peopledatalabs](https://composio.dev/toolkits/peopledatalabs) - Peopledatalabs delivers B2B data enrichment and identity resolution APIs. Supercharge your apps with accurate, up-to-date business and contact data.
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- [Amplitude](https://composio.dev/toolkits/amplitude) - Amplitude is a digital analytics platform for product and behavioral data insights. It helps teams analyze user journeys and make data-driven decisions quickly.
- [Bright Data MCP](https://composio.dev/toolkits/brightdata_mcp) - Bright Data MCP is an AI-powered web scraping and data collection platform. Instantly access public web data in real time with advanced scraping tools.
- [Browseai](https://composio.dev/toolkits/browseai) - Browseai is a web automation and data extraction platform that turns any website into an API. It's perfect for monitoring websites and retrieving structured data without manual scraping.
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- [Coinmarketcal](https://composio.dev/toolkits/coinmarketcal) - CoinMarketCal is a community-powered crypto calendar for upcoming events, announcements, and releases. It helps traders track market-moving developments and stay ahead in the crypto space.
- [Control d](https://composio.dev/toolkits/control_d) - Control d is a customizable DNS filtering and traffic redirection platform. It helps you manage internet access, enforce policies, and monitor usage across devices and networks.
- [Databox](https://composio.dev/toolkits/databox) - Databox is a business analytics platform that connects your data from any tool and device. It helps you track KPIs, build dashboards, and discover actionable insights.
- [Databricks](https://composio.dev/toolkits/databricks) - Databricks is a unified analytics platform for big data and AI on the lakehouse architecture. It empowers data teams to collaborate, analyze, and build scalable solutions efficiently.
- [Datagma](https://composio.dev/toolkits/datagma) - Datagma delivers data intelligence and analytics for business growth and market discovery. Get actionable market insights and track competitors to inform your strategy.
- [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment.
- [Dovetail](https://composio.dev/toolkits/dovetail) - Dovetail is a research analysis platform for transcript review and insight generation. It helps teams code interviews, analyze feedback, and create actionable research summaries.
- [Dub](https://composio.dev/toolkits/dub) - Dub is a short link management platform with analytics and API access. Use it to easily create, manage, and track branded short links for your business.
- [Elasticsearch](https://composio.dev/toolkits/elasticsearch) - Elasticsearch is a distributed, RESTful search and analytics engine for all types of data. It delivers fast, scalable search and powerful analytics across massive datasets.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Serphouse MCP?

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

### Can I use Tool Router MCP with LangChain?

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 Serphouse tools.

### Can I manage the permissions and scopes for Serphouse while using Tool Router?

Yes, absolutely. You can configure which Serphouse 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.

### How safe is my data with Composio Tool Router?

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 Serphouse data and credentials are handled as safely as possible.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)