How to Use the Kontent.ai (Enterprise Headless CMS) MCP in Google ADK

Q: Can my Gemini agent search for specific content items?

Yes, the agent can use getitem to pull metadata for a specific item by its codename. It can also run listitems to scan the entire workspace when analyzing large batches of content.

Feed enterprise CMS data into Gemini's million-token context window using the Google ADK.

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Connect Kontent.ai (Enterprise Headless CMS) MCP to Google ADK

Create your Vinkius account to connect Kontent.ai (Enterprise Headless CMS) 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 Kontent.ai (Enterprise Headless CMS) with Google ADK

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Mass analyze assets and content in Google ADK

The `list_assets` tool lets your agent pull all uploaded media files and documents directly into Gemini's long-context window. You can process hundreds of files at once, extracting metadata and matching assets to specific content items. Combining this with `list_items` allows your agent to cross-reference your entire content library against external datasets in BigQuery. This makes it easy to find gaps in your documentation or identify outdated product pages.

Map complex taxonomy trees to Vertex AI

The `get_taxonomy` tool retrieves nested terms and structural tags from your CMS so your agent can categorize new content accurately. The agent reads the exact taxonomy tree before assigning tags, preventing arbitrary tag creation. You can also call `list_taxonomies` to let your agent see all active categorization groups. This helps your Google Cloud agents organize raw files or external blog imports into the correct CMS categories automatically.

Update localized variants from cloud data

The `upsert_language_variant` tool allows your agent to write translated text or region-specific content directly into your CMS draft fields. The agent writes this data safely without overwriting the top-level container metadata. This MCP Server allows your Gemini agent to read structured data from Google Cloud databases and write it back to your CMS. You don't have to build custom pipelines to keep your product catalog synced with your website.

Setup guide

Set up Kontent.ai (Enterprise Headless CMS) 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 Kontent.ai (Enterprise Headless CMS) 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="Kontent.ai (Enterprise Headless CMS)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Kontent.ai (Enterprise Headless CMS) 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 Kontent.ai. 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 Kontent.ai (Enterprise Headless CMS) MCP in Google ADK

Run pip install google-adk and set up the McpToolset using your HTTP server parameters. Pass this toolset to your LlmAgent constructor to expose the MCP tools to your Gemini models.

Yes, the agent can use get_item to pull metadata for a specific item by its codename. It can also run list_items to scan the entire workspace when analyzing large batches of content.

Yes, the toolset supports both transport types. You can configure the connection parameters to match your infrastructure requirements, whether you are running agents locally or hosting them on Google Cloud.

Yes, you can use the optional tool names filter in the toolset configuration. This allows you to restrict the agent to read-only tools like list_items and block modification tools like publish_variant.

Your content items, taxonomies, and asset metadata are processed in memory and sent directly to your agent. The connection is hosted in a secure, ephemeral V8 isolate on Vinkius, ensuring your MCP connection remains private.

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