How to Use the Frontify MCP in OpenAI Agents SDK

Q: How do I connect the Frontify MCP Server to my OpenAI Agents SDK project?

Just install the SDK, then instantiate the MCPServerStreamableHttp client with the Vinkius URL. Pass that server object to your Agent's constructor, and tools like listworkspaceprojects are discovered automatically.

Q: How can I use the OpenAI Agents SDK and Frontify for a brand migration?

Your agent can read assets from an old system and use patchassetmetadata to apply new tags, descriptions, and copyright info in Frontify. It's much faster than doing it by hand.

Q: What's the best way to list all projects in Frontify with an OpenAI agent?

The listworkspaceprojects tool is what you need. It enumerates all projects within a specified workspace, giving your agent the context to perform other actions.

Build production-grade brand agents with the OpenAI Agents SDK to manage your Frontify assets and users autonomously.

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Connect Frontify MCP to OpenAI Agents SDK

Create your Vinkius account to connect Frontify to OpenAI Agents SDK 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 OpenAI Agents SDK

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Manage and Clean Up Assets Safely

Your agent can now manage your entire Frontify asset library. Use `get_project_assets` to inventory a project, then run bulk updates with `patch_asset_metadata` to fix tagging inconsistencies across thousands of images at once. It's the fastest way to enforce metadata hygiene. For riskier jobs like cleanup, the SDK's built-in guardrails are critical. Your agent can use `wipe_media_asset` to flag old or off-brand content for deletion, but the action won't execute until a human gives the final approval. This prevents accidental deletion of critical brand assets.

Automate User and Workspace Audits

Connect this MCP Server to an OpenAI agent to automate user provisioning and audits. The agent can call `list_platform_users` to get a full user list from Frontify, cross-reference it with your company directory, and flag discrepancies for review. You can also build agent workflows that hand off tasks. For instance, one agent could monitor for new hires, then trigger another specialized agent to grant them access to the right projects using `invite_workspace_user`. All actions are tracked in your OpenAI dashboard.

Run Compliance Checks with your OpenAI Agent

Stop brand drift before it starts. An agent can use `list_brand_guidelines` to get your official rules—colors, fonts, logos—directly from Frontify. It then uses that context to check new assets for compliance. For custom rules not covered in the guidelines, you can use `execute_graphql_payload` to run specific queries against your brand portal. This gives your agent a direct line to the source of truth, ensuring nothing slips through the cracks.

Setup guide

Set up Frontify MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Frontify tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Frontify tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Frontify tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Frontify Agent",
            instructions="You have access to Frontify tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Frontify MCP in OpenAI Agents SDK

Just install the SDK, then instantiate the `MCPServerStreamableHttp` client with the Vinkius URL. Pass that server object to your Agent's constructor, and tools like `list_workspace_projects` are discovered automatically.

Yes. The OpenAI Agents SDK has built-in guardrails. You can configure it to require human approval before executing destructive tools like `wipe_media_asset`, giving you a final check.

Your agent can read assets from an old system and use `patch_asset_metadata` to apply new tags, descriptions, and copyright info in Frontify. It's much faster than doing it by hand.

The `list_workspace_projects` tool is what you need. It enumerates all projects within a specified workspace, giving your agent the context to perform other actions.

The connection exposes asset metadata, project names, and user information for management. Your data is processed in an ephemeral Vinkius sandbox that is destroyed after each session, and your OpenAI API key is stored securely.

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