How to Use the X Ads (Twitter) MCP in Google ADK

Q: Can I list all X Ads (Twitter) accounts using Google ADK?

Yes, the listadaccounts tool handles that. Your agent pulls the full roster of ad accounts and can then pass those IDs to other tools for deeper investigation.

Q: If I want to see recent promotions in X Ads (Twitter) with Google ADK, what tool do I use?

The listpromotedtweets function is what you need. Your agent invokes this tool and gets the list of promoted tweets directly into your working data set for analysis.

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Connect X Ads (Twitter) MCP to Google ADK

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Setup X Ads (Twitter) with Google ADK

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Audit Ad Accounts and Line Items

Use your agent to review every piece of ad infrastructure. The `list_ad_accounts` tool gives you the starting point, letting your agent catalog all relevant accounts. Then, follow up with `list_line_items` to inspect specific creatives or budgets. This is how you build a full audit trail in BigQuery: first list the accounts, then iterate through the line items for each one. It’s designed for deep, structured analysis using Google Cloud infrastructure.

Track Promoted Tweets and Ads

The agent handles complex content auditing by calling `list_promoted_tweets`. This shows every tweet that's been promoted through the system. To get a full picture, you can pair this with `get_ad_account`, which provides the necessary context for those assets. Furthermore, if you need to check out all active ads under an account, simply running `list_ads` delivers the complete list of ad entities.

Get Detailed Performance Analytics

For performance reviews, your agent uses `get_analytics` to pull metrics on various ad entities. You aren't limited to just data; you can also use `list_campaigns` and `list_funding_instruments`. This combination lets your agent build a report that connects spending mechanisms with actual results. This structured approach works great because the resulting data naturally feeds into BigQuery, making it ready for long-context reasoning within Vertex AI.

Setup guide

Set up X Ads (Twitter) 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 X Ads (Twitter) 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="X Ads (Twitter)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to X Ads (Twitter) 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 X Ads (Twitter). 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 X Ads (Twitter) MCP in Google ADK

You configure the MCP toolset with the server's URL. Your agent then treats the tools like native BigQuery or Vertex AI endpoints, allowing it to run queries against ad data.

The server touches ad account details, specifically campaign names and line items. Since you're running this on Google Cloud, all access is logged, providing a traceable record of what your agent viewed.

Yes, the `list_ad_accounts` tool handles that. Your agent pulls the full roster of ad accounts and can then pass those IDs to other tools for deeper investigation.

The `list_promoted_tweets` function is what you need. Your agent invokes this tool and gets the list of promoted tweets directly into your working data set for analysis.

It does. By integrating with BigQuery, it supports long-context reasoning—you can process massive amounts of ad and analytics data in a single workflow.

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