How to Use the LinkedIn Ads MCP in Google ADK

Q: Can I use Google ADK to analyze LinkedIn Ads creatives with BigQuery data?

Yes, your agent can fetch active assets using listcreatives and join that data with offline sales pipelines in BigQuery. This lets Gemini analyze which ad variations are driving actual enterprise pipeline value.

Feed massive LinkedIn Ads performance histories directly into Gemini's million-token context window using the Google ADK.

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Connect LinkedIn Ads MCP to Google ADK

Create your Vinkius account to connect LinkedIn Ads to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup LinkedIn Ads with Google ADK

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Enterprise Gemini reasoning over LinkedIn Ads data

The LinkedIn Ads MCP Server gives your Google ADK agents direct access to performance metrics via `get_account_analytics` and `get_campaign_analytics`. By feeding Gemini's million-token context window, your enterprise agent can analyze years of historical B2B ad spend alongside your internal BigQuery data tables. You pass the entire LinkedIn campaign history directly into Gemini's prompt context. The agent processes the complete LinkedIn performance dataset, identifies B2B attribution patterns, and outputs structured bidding recommendations inside your Google Cloud environment.

Cross-reference BigQuery tables with active creatives

The LinkedIn Ads MCP Server exposes `list_creatives` and `list_campaigns` to your Google ADK agent, enabling real-time alignment with your enterprise data warehouse. Your agent can query active creative variations and cross-reference their IDs against offline conversion data stored in BigQuery. This setup allows you to build autonomous closed-loop LinkedIn optimization pipelines within Vertex AI. The agent identifies which creative assets drove actual pipeline revenue in your warehouse and uses `enable_campaign` to scale the winning variations.

Google ADK tool filtering for safe enterprise deployment

The LinkedIn Ads MCP Server supports strict tool-level filtering when initialized through the Google ADK framework. You can restrict your agent's access to read-only capabilities like `get_account_info` and `list_campaign_groups` in your production Python code. This restriction ensures that junior Google Cloud agents cannot accidentally execute budget-altering LinkedIn commands. If you decide to grant execution rights later, you simply update the tool names filter to expose `pause_campaign` to your authorized optimization loops.

Setup guide

Set up LinkedIn Ads MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with LinkedIn Ads tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="LinkedIn Ads_agent",
    model="gemini-2.0-flash",
    instruction="You have access to LinkedIn Ads tools via MCP.",
    tools=mcp_tools,
)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by LinkedIn 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 LinkedIn Ads MCP in Google ADK

Import the toolset module from the ADK and pass your Vinkius HTTP endpoint as the transport parameter. Add this toolset to your agent initialization to immediately expose tools like `list_campaigns` to Gemini.

Yes, your agent can fetch active assets using `list_creatives` and join that data with offline sales pipelines in BigQuery. This lets Gemini analyze which ad variations are driving actual enterprise pipeline value.

Pass a list of allowed tool names to your toolset constructor in Python. By omitting `pause_campaign` and `enable_campaign`, you guarantee the agent only performs analytics queries using `get_campaign_analytics`.

Yes, you can feed extensive campaign histories retrieved from `get_account_analytics` directly into Gemini's context. The model can process thousands of rows of performance data in a single turn.

Your campaign metrics, creative assets, and account info pass through the Vinkius V8 secure sandbox directly to your Google Cloud environment. No data is stored on external servers, keeping your proprietary B2B marketing spend metrics isolated within your cloud project.

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