How to Use the Eventbrite MCP in Google ADK

Q: How do I connect my Gemini agent in Google ADK to this Eventbrite MCP server?

You use the McpToolset class, providing it the server URL from your Vinkius account. That toolset is then passed into your LlmAgent constructor. You can optionally filter which tools the agent has access to.

Q: Can a Google ADK agent sync Eventbrite ticket orders to a BigQuery table?

Yes. Your agent can use the listeventticketorders tool to fetch transaction data and then use a separate BigQuery tool to insert it. The agent acts as the go-between, handling the data transformation in its own logic.

Q: How do I see past event data?

Use the listpastcompletedevents tool. Your agent can call this to get a list of all your finished events, then use the event IDs from that list to get specific performance details with other tools.

Q: Is my Eventbrite sales data secure when using Google ADK?

Yes. When your agent calls tools like geteventperformancesummary or listeventticketorders, the data flows through Vinkius's secure, ephemeral environment. The connection is authenticated by your private token, and the data isn't persisted on the MCP server itself.

Let your Gemini agent analyze Eventbrite data at scale using the Google ADK and your existing cloud stack.

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Connect Eventbrite MCP to Google ADK

Create your Vinkius account to connect Eventbrite 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 Eventbrite with Google ADK

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Feed Eventbrite data into BigQuery

This is about feeding your cloud. A Gemini agent can use its long context window to pull complete reports from multiple events using `list_event_ticket_orders` and `list_event_attendees`. From there, the agent's job is to structure that data and push it into a BigQuery table. You don't need a separate ETL pipeline. Your agent becomes the bridge between your live event operations and your data warehouse.

Build a real-time ops dashboard in Vertex AI

Your agent can monitor your entire Eventbrite presence. It starts by getting a list of your organizations with `list_my_organizations` and then runs `list_currently_live_events` for each one. With that list, it can loop through and get performance data using `get_event_performance_summary`. This data can be streamed to a Vertex AI dashboard, giving you a single pane of glass for every event you're running, powered by your agent.

Get detailed event briefings with this MCP Server

Before a major event, you need all the details in one place. Your Google ADK agent can get them. It calls `get_event_detailed_data` to see the event's setup, capacity, and custom questions. Then, it pulls the latest registration numbers with `quick_event_volume_audit`. Because Gemini can hold all this context, you can simply ask it to summarize the event's status, and it will synthesize the data from both tools into a clean report.

Setup guide

Set up Eventbrite 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 Eventbrite 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="Eventbrite_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Eventbrite 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 Eventbrite. 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 Eventbrite MCP in Google ADK

You use the `McpToolset` class, providing it the server URL from your Vinkius account. That toolset is then passed into your `LlmAgent` constructor. You can optionally filter which tools the agent has access to.

Yes. Your agent can use the `list_event_ticket_orders` tool to fetch transaction data and then use a separate BigQuery tool to insert it. The agent acts as the go-between, handling the data transformation in its own logic.

It's the native integration with your Google Cloud infrastructure. If your data lives in BigQuery and you use Vertex AI for models, using a Google ADK agent to pull in Eventbrite data via this MCP toolset is a natural fit. It keeps everything in one ecosystem.

Use the `list_past_completed_events` tool. Your agent can call this to get a list of all your finished events, then use the event IDs from that list to get specific performance details with other tools.

Yes. When your agent calls tools like `get_event_performance_summary` or `list_event_ticket_orders`, the data flows through Vinkius's secure, ephemeral environment. The connection is authenticated by your private token, and the data isn't persisted on the MCP server itself.

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