How to Use the Google Ads MCP in AutoGen
Let your AutoGen agents debate Google Ads performance and coordinate budget changes.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Google Ads MCP to AutoGen
Create your Vinkius account to connect Google Ads to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Let AutoGen agents debate Google Ads performance
The `get_ad_performance` tool feeds live Google Ads creative metrics directly into your AutoGen multi-agent conversation. An AutoGen performance analyst agent can review these Google Ads metrics and argue for pausing low-performing creatives, while a creative agent defends the copy. This structured AutoGen debate ensures you don't make rash decisions based on short-term Google Ads statistical noise. You configure these AutoGen agents to use this Google Ads MCP Server to settle disputes with raw data. By requiring AutoGen consensus before any Google Ads strategy shift, you prevent individual agents from making uncoordinated changes. The AutoGen conversation continues until both agents agree on the best Google Ads optimization path.
Coordinate budget shifts via consensus
The `list_campaigns` tool provides a complete list of active campaigns to your AutoGen budget committee. One AutoGen agent analyzes high-performing campaigns using `get_campaign_report`, while another checks overall Google Ads account limits. They negotiate how to distribute remaining Google Ads funds to maximize conversion volume across your AutoGen framework. This AutoGen multi-agent setup ensures that Google Ads budget reallocations don't happen in a vacuum. The AutoGen agents cross-reference Google Ads campaign details with historical performance to avoid over-allocating to volatile keywords. You get a balanced, logical Google Ads budget strategy driven by automated AutoGen deliberation.
Validate keyword strategies with an MCP Server
The `get_keyword_performance` tool gives your AutoGen agents the exact metrics they need to evaluate Google Ads search term efficiency. A search specialist AutoGen agent proposes new keyword targets, while a finance agent checks the Google Ads cost per conversion. This AutoGen negotiation keeps your keyword expansion strategy aligned with your actual Google Ads acquisition costs. By using the AutoGen McpToolAdapter, the framework automatically maps these Google Ads tool schemas to your agents' capabilities. The AutoGen agents query `search_keywords` to find new Google Ads opportunities and debate their relevance before recommending them. It turns Google Ads keyword research into a collaborative, data-validated process inside your AutoGen workflow.
Set up Google Ads MCP in AutoGen
Prerequisites
- Python 3.10+ installed
-
autogen-ext[mcp]package - Active Vinkius subscription with a valid endpoint token
- 1
Install AutoGen with MCP
Run
pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includesmcp_server_toolsfor stateless tool access. - 2
Fetch tools from the MCP
Call
mcp_server_tools(SseServerParams(url=...))with your Vinkius endpoint. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. - 3
Run your agent
Pass the tools to
AssistantAgentand callagent.run(). The agent invokes Google Ads tools and returns structured results.
from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
server_params = SseServerParams(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
tools = await mcp_server_tools(server_params)
agent = AssistantAgent(
name="Google Ads_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Google Ads data")
print(result.messages[-1].content) Prerequisites
- Python 3.10+ installed
-
autogen-ext[mcp]+autogen-agentchat - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Same packages as above.
McpWorkbenchis ideal when your agent needs stateful sessions across multiple tool calls. - 2
Use McpWorkbench as context manager
Wrap your agent in
async with McpWorkbench(...)to maintain shared state and resources. The workbench manages the full MCP session lifecycle. - 3
Run with workbench
Pass
workbench=workbenchto your agent. State is preserved across multiple tool calls within the same session.
from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
server_params = SseServerParams(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
async with McpWorkbench(server_params) as workbench:
agent = AssistantAgent(
name="Google Ads_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Google Ads data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Google Ads. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Common questions about Google Ads MCP in AutoGen
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