How to Use the Unbounce MCP in Google ADK

Q: How does the Google ADK help with Unbounce page management?

The pages tool lets your agent list all landing pages, providing a structured overview of assets. This data is immediately available for long-context processing within Gemini models.

Q: Can I use the Google ADK to analyze Unbounce lead performance?

Absolutely. By using the leads tool, your agent pulls submission records that can be fed into BigQuery and analyzed for deep insights on user behavior.

Q: What is the scope of Unbounce sub-accounts via the Google ADK?

The subaccounts tool gives you a complete list of accessible sub-accounts. Your agent can then apply consistent rules or check permissions across all of them.

Manage Unbounce campaigns using the Google ADK, connecting to BigQuery data streams.

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Connect Unbounce MCP to Google ADK

Create your Vinkius account to connect Unbounce 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 Unbounce with Google ADK

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View all existing Unbounce landing pages

The `pages` tool lets your agent list every available page within Unbounce. It gets you a clear view of what assets are ready for optimization or testing. Since this connects to Google Cloud infrastructure, the data returned is immediately structured and ready for BigQuery analysis.

Gather lead submission records from your pages

You can use `leads` to pull all submissions tied to a specific landing page. This isn't just a list; it’s actionable data that feeds directly into Vertex AI for deeper modeling. The agent treats this as structured input, enabling complex reasoning about conversion paths and performance metrics.

Check Unbounce sub-account access

The `sub_accounts` tool enumerates all accessible sub-accounts. This is useful for large enterprises where marketing efforts are segmented by department or geography. The agent can verify permissions and scope its actions across the entire organizational structure before making changes.

Setup guide

Set up Unbounce 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 Unbounce 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="Unbounce_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Unbounce tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Unbounce MCP in Google ADK

The `pages` tool lets your agent list all landing pages, providing a structured overview of assets. This data is immediately available for long-context processing within Gemini models.

Absolutely. By using the `leads` tool, your agent pulls submission records that can be fed into BigQuery and analyzed for deep insights on user behavior.

The `sub_accounts` tool gives you a complete list of accessible sub-accounts. Your agent can then apply consistent rules or check permissions across all of them.

Yes, that's its core function. It’s built natively to connect with BigQuery and Vertex AI, meaning your marketing data never stays siloed.

The tool retrieves lead submission data, including contact details and timestamps. This structured information allows for advanced pattern recognition within your enterprise agents.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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