How to Use the Artsy MCP in Google ADK

Q: Can I filter which Artsy tools my Google ADK agent can access?

Yes, use the toolnames parameter in your toolset configuration. This lets you limit the agent to specific tools like listartworks while blocking others.

Feed global art database records directly into your Google ADK enterprise pipelines and Gemini models.

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Connect Artsy MCP to Google ADK

Create your Vinkius account to connect Artsy 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 Artsy with Google ADK

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Query the Artsy MCP Server using Gemini long-context

The Artsy MCP Server gives your Google ADK agents the ability to search millions of creative works using `search_artsy`. Gemini models process these massive search payloads within their million-token context windows. You can feed entire gallery catalogs directly into the agent for deep analysis. Enterprise pipelines benefit from this because they do not need to chunk the incoming art metadata. The agent reads the raw API output and extracts patterns instantly.

Analyze gallery exhibition trends in BigQuery

Your Google ADK workflow uses `list_fairs` and `list_shows` to extract exhibition schedules. You can pipe this raw art data directly into BigQuery for trend forecasting. The agent acts as the bridge between the live art world and your analytical database. This setup eliminates manual data entry for art market analysts. Your agent runs the tools, formats the output, and updates your Google Cloud storage bucket automatically.

Extract detailed artist metadata for Vertex AI models

Pull complete records using `get_artist_details` to feed your custom Vertex AI classification models. The Google ADK toolset lets you restrict which tools are active using the tool_names filter. This ensures your agent only queries specific artist profiles during training cycles. By limiting the scope, you save on API costs and prevent model drift. The agent gets clean, structured JSON to parse and send to your machine learning pipeline.

Setup guide

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

Initialize McpToolset with the Artsy MCP server URL in your Python script. Pass this toolset directly to your LlmAgent to let Gemini call the tools.

Yes, use the tool_names parameter in your toolset configuration. This lets you limit the agent to specific tools like list_artworks while blocking others.

Gemini uses its long context to analyze multiple outputs from list_shows simultaneously. It identifies overlapping artists across different global exhibitions.

Yes, you can run the agent in a Cloud Function or Cloud Run. It connects to the Artsy server over secure HTTP transport.

All metadata fetched from the art database is processed within your private Google Cloud VPC. The MCP Vinkius sandbox ensures that no search history or API payloads are cached or exposed.

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