# How to integrate Google search console MCP with Autogen

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

## Introduction

This guide walks you through connecting Google search console to AutoGen 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 AutoGen 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)
- [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 required dependencies for Autogen and Composio
- Initialize Composio and create a Tool Router session for Google search console
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call Google search console tools
- Run a live chat loop where you ask the agent to perform Google search console operations

## What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.
Key features include:
- Multi-Agent Systems: Build collaborative agent workflows
- MCP Workbench: Native support for Model Context Protocol tools
- Streaming HTTP: Connect to external services through streamable HTTP
- AssistantAgent: Pre-built agent class for tool-using assistants

## 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 agents and assistants directly to Google search console. Instead of manually wiring Google search console APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely.
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

You will need:
- A Composio API key
- An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
- A Google search console account you can connect to Composio
- Some basic familiarity with Autogen and Python async

### 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

Install Composio, Autogen extensions, and dotenv.
What's happening:
- composio connects your agent to Google search console via MCP
- autogen-agentchat provides the AssistantAgent class
- autogen-ext-openai provides the OpenAI model client
- autogen-ext-tools provides MCP workbench support
```bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools
```

### 3. Set up environment variables

Create a .env file in your project folder.
What's happening:
- COMPOSIO_API_KEY is required to talk to Composio
- OPENAI_API_KEY is used by Autogen's OpenAI client
- USER_ID is how Composio identifies which user's Google search console connections to use
```bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com
```

### 4. Import dependencies and create Tool Router session

What's happening:
- load_dotenv() reads your .env file
- Composio(api_key=...) initializes the SDK
- create(...) creates a Tool Router session that exposes Google search console tools
- session.mcp.url is the MCP endpoint that Autogen will connect to
```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Google search console session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["google_search_console"]
    )
    url = session.mcp.url
```

### 5. Configure MCP parameters for Autogen

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.
What's happening:
- url points to the Tool Router MCP endpoint from Composio
- timeout is the HTTP timeout for requests
- sse_read_timeout controls how long to wait when streaming responses
- terminate_on_close=True cleans up the MCP server process when the workbench is closed
```python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)
```

### 6. Create the model client and agent

What's happening:
- OpenAIChatCompletionClient wraps the OpenAI model for Autogen
- McpWorkbench connects the agent to the MCP tools
- AssistantAgent is configured with the Google search console tools from the workbench
```python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Google search console assistant agent with MCP tools
    agent = AssistantAgent(
        name="google_search_console_assistant",
        description="An AI assistant that helps with Google search console operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )
```

### 7. Run the interactive chat loop

What's happening:
- The script prompts you in a loop with You:
- Autogen passes your input to the model, which decides which Google search console tools to call via MCP
- agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
- Typing exit, quit, or bye ends the loop
```python
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")

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

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

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
```

## Complete Code

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

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Google search console session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["google_search_console"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Google search console assistant agent with MCP tools
        agent = AssistantAgent(
            name="google_search_console_assistant",
            description="An AI assistant that helps with Google search console operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        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")

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

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

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

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

## Conclusion

You now have an Autogen assistant wired into Google search console through Composio's Tool Router and MCP. From here you can:
- Add more toolkits to the toolkits list, for example notion or hubspot
- Refine the agent description to point it at specific workflows
- Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Google search console, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

## 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)
- [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)

## Related Toolkits

- [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. It's the go-to tool for calculations, reporting, and flexible data management.
- [21risk](https://composio.dev/toolkits/_21risk) - 21RISK is a web app built for easy checklist, audit, and compliance management. It streamlines risk processes so teams can focus on what matters.
- [Abstract](https://composio.dev/toolkits/abstract) - Abstract provides a suite of APIs for automating data validation and enrichment tasks. It helps developers streamline workflows and ensure data quality with minimal effort.
- [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time.
- [Agenty](https://composio.dev/toolkits/agenty) - Agenty is a web scraping and automation platform for extracting data and automating browser tasks—no coding needed. It streamlines data collection, monitoring, and repetitive online actions.
- [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 Autogen?

Yes, you can. Autogen 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.

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