How to Use the Frontify MCP in Google ADK

Q: How do I start using the Frontify tools with Google ADK?

After installing the ADK, create an McpToolset instance pointing to your Vinkius server URL. Then, just add that toolset to your LlmAgent's tools list to get started.

Q: How does the Google ADK help my team enforce brand guidelines in Frontify?

Your agent can fetch the rules using listbrandguidelines. With Gemini's reasoning capabilities, it can then analyze asset metadata from getprojectassets to check for compliance.

Use Google ADK to build Gemini agents that connect your BigQuery data with your Frontify brand assets.

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Connect Frontify MCP to Google ADK

Create your Vinkius account to connect Frontify 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 Frontify with Google ADK

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Audit Entire Libraries in One Go

Gemini's long-context window changes the game for asset audits. Your agent can call `get_project_assets` and `list_workspace_projects` to pull metadata for tens of thousands of assets and hold it all in context for analysis. No more batching or losing track. This lets you cross-reference your entire Frontify library against a product list in BigQuery or a campaign plan in Google Sheets. Your agent can find every asset related to a discontinued product and flag it for archival in a single pass.

Sync Google Workspace with Frontify

Stop managing user permissions in two places. Build a Google ADK agent that uses `list_platform_users` to read your current user list from Frontify. The agent can then compare that list to a Google Workspace group and automatically provision new accounts with `invite_workspace_user` or flag users who should be removed. It's a direct way to keep your brand portal access in sync with your central identity provider.

Query Frontify from your Google ADK Agent

Sometimes you need to ask a very specific question. The `execute_graphql_payload` tool lets your Gemini agent run raw GraphQL queries against Frontify for anything not covered by the standard tools. You can also build monitoring agents that periodically check your API usage with `get_account_limits` and log the results to Google Cloud Logging. This helps you manage costs and prevent service interruptions across your Google Cloud-based infrastructure.

Setup guide

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

After installing the ADK, create an `McpToolset` instance pointing to your Vinkius server URL. Then, just add that toolset to your `LlmAgent`'s `tools` list to get started.

Yes, that's a primary use case. The agent can query for asset performance data in BigQuery and then use `patch_asset_metadata` in Frontify to tag assets based on the results.

Your agent can fetch the rules using `list_brand_guidelines`. With Gemini's reasoning capabilities, it can then analyze asset metadata from `get_project_assets` to check for compliance.

It's a perfect match. You can pull massive lists of assets or users from Frontify and analyze the entire dataset in one prompt without needing complex state management.

Your agent will handle Frontify asset metadata and user lists. The Vinkius MCP Server operates on a zero-trust model, processing requests in isolated environments, while your data is protected by Google Cloud's own robust security controls.

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