How to integrate Google Ads MCP with Autogen

This guide walks you through connecting Google Ads to AutoGen using the Composio tool router. By the end, you'll have a working Google Ads agent that can create a new customer list for holiday campaigns, get campaign details by campaign id, list all current customer lists in your account through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Google Ads account through Composio's Google Ads MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Google Ads is Google's online advertising platform for creating, managing, and optimizing digital campaigns. It helps businesses reach targeted customers and maximize return on ad spend.

9 Tools

Introduction

This guide walks you through connecting Google Ads to AutoGen using the Composio tool router. By the end, you'll have a working Google Ads agent that can create a new customer list for holiday campaigns, get campaign details by campaign id, list all current customer lists in your account through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a Google Ads account through Composio's Google Ads MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Google Ads with

ChatGPTOpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenCodeCursorVS CodeOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

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 Ads
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Google Ads tools
  • Run a live chat loop where you ask the agent to perform Google Ads 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 Ads MCP server, and what's possible with it?

The Google Ads 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 Ads account. It provides structured and secure access to your advertising data, so your agent can perform actions like creating customer lists, retrieving campaign details, and managing audience segments on your behalf.

  • Automated customer list creation: Instantly have your agent create new customer lists for targeted marketing campaigns, streamlining your segmentation workflows.
  • Campaign insights by ID or name: Let your agent fetch detailed information for any ad campaign using its ID or name, making reporting and optimization a breeze.
  • Customer list management: Ask your agent to retrieve and review all your existing customer lists, so you always know who you're targeting.
  • Add or remove contacts from lists: Seamlessly update audience membership by having your agent add or remove contacts from specified customer lists for more dynamic targeting.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Google Ads account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Google Ads via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

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 Ads connections to use
5

Import dependencies and create Tool Router session

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 Ads session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["googleads"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Google Ads tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

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")}
)

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
7

Create the model client and agent

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 Ads assistant agent with MCP tools
    agent = AssistantAgent(
        name="googleads_assistant",
        description="An AI assistant that helps with Google Ads operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Google Ads tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Google Ads 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")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Google Ads 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

Complete Code

Here's the complete code to get you started with Google Ads and AutoGen:

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 Ads session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["googleads"]
    )
    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 Ads assistant agent with MCP tools
        agent = AssistantAgent(
            name="googleads_assistant",
            description="An AI assistant that helps with Google Ads 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 Ads 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 Ads 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 Ads, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

Every Google Ads action and event your agent gets out of the box.

Add or remove to customer list

AddOrRemoveToCustomerList Tool will add a contact to a customer list in Google Ads.

Create customer list

Creates a customer list in Google Ads.

Get Campaign By Id

GetCampaignById Tool returns details of a campaign in Google Ads.

Get campaign by name

Queries Google Ads via SQL to retrieve a campaign by its exact name.

Get customer lists

GetCustomerLists Tool lists all customer lists (audience/remarketing lists) in Google Ads.

List Accessible Customers

ListAccessibleCustomers retrieves all Google Ads customer accounts accessible to the authenticated user.

Mutate Ad Groups

Create, update, or remove ad groups within Google Ads campaigns.

Mutate Campaigns

Create, update, or remove Google Ads campaigns in batch.

Search Stream GAQL

Execute a Google Ads Query Language (GAQL) query and stream all results in a single response.

FRAMEWORKS

How to build Google Ads MCP Agent with another framework

ChatGPT logo

ChatGPT

Use Google Ads MCP with ChatGPT

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Google Ads MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Google Ads MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Google Ads MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Google Ads MCP with Claude Cowork

Codex logo

Codex

Use Google Ads MCP with Codex

Cursor logo

Cursor

Use Google Ads MCP with Cursor

OpenClaw logo

OpenClaw

Use Google Ads MCP with OpenClaw

Hermes logo

Hermes

Use Google Ads MCP with Hermes

CLI logo

CLI

Use Google Ads MCP with CLI

Google ADK logo

Google ADK

Use Google Ads MCP with Google ADK

LangChain logo

LangChain

Use Google Ads MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Google Ads MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Google Ads MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Google Ads MCP with LlamaIndex

CrewAI logo

CrewAI

Use Google Ads MCP with CrewAI

OpenCode logo

OpenCode

Use Google Ads MCP with OpenCode

VS Code logo

VS Code

Use Google Ads MCP with VS Code

FAQ

Frequently asked questions

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

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 Ads tools.

Yes, absolutely. You can configure which Google Ads scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Google Ads data and credentials are handled as safely as possible.

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