# How to integrate Google search console MCP with LangChain

```json
{
  "title": "How to integrate Google search console MCP with LangChain",
  "toolkit": "Google search console",
  "toolkit_slug": "google_search_console",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/google_search_console/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/google_search_console/framework/langchain.md",
  "updated_at": "2026-05-12T10:13:44.771Z"
}
```

## Introduction

This guide walks you through connecting Google search console to LangChain using the Composio tool router. By the end, you'll have a working Google search console agent that can fetch last week's top search queries, inspect indexing status for this url, list all sitemaps for your site through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Google search console account through Composio's Google search console MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Google search console with

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

## TL;DR

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

The Google search console MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Google Search Console account. It provides structured and secure access to your website’s search analytics and indexing data, so your agent can retrieve site lists, inspect URLs, manage sitemaps, and run detailed search performance queries on your behalf.
- Comprehensive site and sitemap management: Have your agent list all properties you own, fetch details about specific sitemaps, or submit new sitemaps for indexing to keep Google up to date.
- Automated URL inspection: Let your agent check the indexing status and uncover crawl or indexing issues for any URL in your properties, so you can spot and resolve problems quickly.
- Instant search analytics reporting: Ask your agent to pull granular performance metrics such as clicks, impressions, CTR, and average position for any site, page, or query segment.
- Bulk site and sitemap overview: Effortlessly retrieve a list of all sites and their associated sitemaps, making it easy to monitor your web presence at scale.
- Proactive index issue detection: Enable your agent to routinely review URLs and sitemaps for errors or warnings, helping you stay ahead of SEO issues without manual digging.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `GOOGLE_SEARCH_CONSOLE_ADD_SITE` | Add Site | Adds a site to the set of the user's sites in Google Search Console. This action registers a new property (site) in Google Search Console for the authenticated user. After adding the site, you will need to verify ownership through one of the available verification methods. The site URL must be properly formatted as either a URL-prefix property (with protocol) or a domain property (with sc-domain prefix). |
| `GOOGLE_SEARCH_CONSOLE_DELETE_SITE` | Delete Site | Removes a site from the user's Google Search Console sites. This action permanently removes a site property from the authenticated user's Search Console account. The site URL must be URL-encoded. Use this when you need to unregister a site from tracking in Search Console. |
| `GOOGLE_SEARCH_CONSOLE_GET_SITE` | Get Site | Retrieves information about a specific Search Console site. Use when you need to get site details including permission level for a specific property. |
| `GOOGLE_SEARCH_CONSOLE_GET_SITEMAP` | Get Sitemap | Retrieves sitemap metadata (submitted/indexed counts, errors, warnings, last-submission timestamps) for a specific sitemap in Search Console. Returns metadata only, not raw XML content. Note: numeric fields like `errors`, `warnings`, `submitted`, and `indexed` may be returned as strings; cast to int before comparisons. Values such as `contents.indexed` can lag several days after submission. |
| `GOOGLE_SEARCH_CONSOLE_INSPECT_URL` | Inspect URL | Inspects a URL for indexing issues and status in Google Search Console. Results may reflect cached data lagging real changes by several days. High-volume use can trigger 429 quota errors; limit to priority URLs. |
| `GOOGLE_SEARCH_CONSOLE_LIST_SITEMAPS` | List Sitemaps | Lists all sitemaps for a site in Google Search Console. Response fields `errors`, `warnings`, `contents.submitted`, and `contents.indexed` may be returned as strings; cast to integers before numeric operations. Evaluate these fields alongside `isPending` for sitemap health. |
| `GOOGLE_SEARCH_CONSOLE_LIST_SITES` | List Sites | Lists all verified sites (properties) owned by the authenticated user in Google Search Console. Response contains a siteEntry array — always iterate it, never assume a single object. Each entry includes permissionLevel, which varies per site; do not assume owner-level access for all returned properties. When calling downstream tools, use the site_url value exactly as returned, including protocol, subdomain, sc-domain: prefix, and trailing slash — any deviation causes empty results or permission errors. Empty siteEntry may indicate missing OAuth scopes or no verified properties. Newly added properties may not appear immediately due to propagation delay. |
| `GOOGLE_SEARCH_CONSOLE_SEARCH_ANALYTICS_QUERY` | Search Analytics Query | Queries Google Search Console for search analytics data including clicks, impressions, CTR, and position metrics. Only returns URLs with at least one impression; missing rows do not confirm non-indexing. Position is an impression-weighted average rank. |
| `GOOGLE_SEARCH_CONSOLE_SUBMIT_SITEMAP` | Submit Sitemap | Submits a sitemap to Google Search Console for indexing. This action registers or resubmits a sitemap for a verified property in Google Search Console. The sitemap file must be accessible at the specified URL and properly formatted as XML. Supported sitemap types include standard sitemaps, sitemap index files, RSS feeds, and Atom feeds. The authenticated user must have site owner or full user permissions for the property. After submission, Google will crawl and process the sitemap according to its standard indexing schedule. |

## Supported Triggers

None listed.

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

The Google search console MCP server is an implementation of the Model Context Protocol that connects your AI agent to Google search console. It provides structured and secure access so your agent can perform Google search console 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 Google search console 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 Google search console 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 Google search console tools as needed
```python
# Create Tool Router session for Google search console
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['google_search_console']
)

url = session.mcp.url
```

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

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

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

No description provided.
```python
client = MultiServerMCPClient({
    "google_search_console-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({
    "google_search_console-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 Google search console 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 Google search console 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=['google_search_console']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "google_search_console-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 Google search console 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: ['google_search_console']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "google_search_console-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 Google search console 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 Google search console 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 Google search console MCP Agent with another framework

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

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- [Ambee](https://composio.dev/toolkits/ambee) - Ambee is an environmental data platform providing real-time, hyperlocal APIs for air quality, weather, and pollen. Get precise environmental insights to power smarter decisions in your apps and workflows.
- [Ambient weather](https://composio.dev/toolkits/ambient_weather) - Ambient Weather is a platform for personal weather stations with a robust API for accessing local, real-time, and historical weather data. Get detailed environmental insights directly from your own sensors for smarter apps and automations.
- [Anonyflow](https://composio.dev/toolkits/anonyflow) - Anonyflow is a service for encryption-based data anonymization and secure data sharing. It helps organizations meet GDPR, CCPA, and HIPAA data privacy compliance requirements.
- [Api ninjas](https://composio.dev/toolkits/api_ninjas) - Api ninjas offers 120+ public APIs spanning categories like weather, finance, sports, and more. Developers use it to supercharge apps with real-time data and actionable endpoints.
- [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots.
- [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. It lets you automate data extraction and workflow tasks at scale—no infrastructure headaches.
- [Autom](https://composio.dev/toolkits/autom) - Autom is a lightning-fast search engine results data platform for Google, Bing, and Brave. Developers use it to access fresh, low-latency SERP data on demand.
- [Beaconchain](https://composio.dev/toolkits/beaconchain) - Beaconchain is a real-time analytics platform for Ethereum 2.0's Beacon Chain. It provides detailed insights into validators, blocks, and overall network performance.
- [Big data cloud](https://composio.dev/toolkits/big_data_cloud) - BigDataCloud provides APIs for geolocation, reverse geocoding, and address validation. Instantly access reliable location intelligence to enhance your applications and workflows.
- [Bigpicture io](https://composio.dev/toolkits/bigpicture_io) - BigPicture.io offers APIs for accessing detailed company and profile data. Instantly enrich your applications with up-to-date insights on 20M+ businesses.
- [Bitquery](https://composio.dev/toolkits/bitquery) - Bitquery is a blockchain data platform offering indexed, real-time, and historical data from 40+ blockchains via GraphQL APIs. Get unified, reliable access to complex on-chain data for analytics, trading, and research.
- [Brightdata](https://composio.dev/toolkits/brightdata) - Brightdata is a leading web data platform offering advanced scraping, SERP APIs, and anti-bot tools. It lets you collect public web data at scale, bypassing blocks and friction.
- [Builtwith](https://composio.dev/toolkits/builtwith) - BuiltWith is a web technology profiler that uncovers the technologies powering any website. Gain actionable insights into analytics, hosting, and content management stacks for smarter research and lead generation.
- [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation.
- [Cabinpanda](https://composio.dev/toolkits/cabinpanda) - Cabinpanda is a data collection platform for building and managing online forms. It helps streamline how you gather, organize, and analyze responses.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Google search console MCP?

With a standalone Google search console MCP server, the agents and LLMs can only access a fixed set of Google search console tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Google search console 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 Google search console tools.

### Can I manage the permissions and scopes for Google search console while using Tool Router?

Yes, absolutely. You can configure which Google search console 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 Google search console data and credentials are handled as safely as possible.

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