# How to integrate Google search console MCP with OpenAI Agents SDK

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

## Introduction

This guide walks you through connecting Google search console to the OpenAI Agents SDK 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 OpenAI Agents SDK 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)
- [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)
- [LangChain](https://composio.dev/toolkits/google_search_console/framework/langchain)
- [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
- Install the necessary dependencies
- Initialize Composio and create a Tool Router session for Google search console
- Configure an AI agent that can use Google search console as a tool
- Run a live chat session where you can ask the agent to perform Google search console operations

## What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.
Key features include:
- Hosted MCP Tools: Connect to external services through hosted MCP endpoints
- SQLite Sessions: Persist conversation history across interactions
- Simple API: Clean interface with Agent, Runner, and tool configuration
- Streaming Support: Real-time response streaming for interactive applications

## 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

Before starting, make sure you have:
- Composio API Key and OpenAI API Key
- Primary know-how of OpenAI Agents SDK
- A live Google search console project
- Some knowledge of Python or Typescript

### 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).
- Go to Settings and copy your API key.

### 2. Install dependencies

Install the Composio SDK and the OpenAI Agents SDK.
```python
pip install composio_openai_agents openai-agents python-dotenv
```

```typescript
npm install @composio/openai-agents @openai/agents dotenv
```

### 3. Set up environment variables

Create a .env file and add your OpenAI and Composio API keys.
```bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com
```

### 4. Import dependencies

What's happening:
- You're importing all necessary libraries.
- The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Google search console.
```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
```

### 5. Set up the Composio instance

No description provided.
```python
load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
```

```typescript
dotenv.config();

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

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
```

### 6. Create a Tool Router session

What is happening:
- You give the Tool Router the user id and the toolkits you want available. Here, it is only google_search_console.
- The router checks the user's Google search console connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access Google search console.
- This approach keeps things lightweight and lets the agent request Google search console tools only when needed during the conversation.
```python
# Create a Google search console Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["google_search_console"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for Google search console
const session = await composio.create(userId as string, {
  toolkits: ['google_search_console'],
});
const mcpUrl = session.mcp.url;
```

### 7. Configure the agent

No description provided.
```python
# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Google search console. "
        "Help users perform Google search console operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
```

```typescript
// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access Google search console. Help users perform Google search console operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
```

### 8. Start chat loop and handle conversation

No description provided.
```python
print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

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

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

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

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

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

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["google_search_console"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Google search console. "
        "Help users perform Google search console operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

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

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['google_search_console'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access Google search console. Help users perform Google search console operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

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

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

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

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\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

This was a starter code for integrating Google search console MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Google search console.
Key features:
- Hosted MCP tool integration through Composio's Tool Router
- SQLite session persistence for conversation history
- Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

## How to build Google search console MCP Agent with another framework

- [ChatGPT](https://composio.dev/toolkits/google_search_console/framework/chatgpt)
- [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)
- [LangChain](https://composio.dev/toolkits/google_search_console/framework/langchain)
- [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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- [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 OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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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