How to Use the Kontent.ai MCP in Google ADK

Q: How do I configure Kontent.ai with Google ADK?

Install google-adk via pip. Create a McpToolset using StreamableHttpServerParameters with your Vinkius URL, then pass it to the LlmAgent under the tools argument.

Q: Can Google ADK restrict which Kontent.ai tools are available?

Yes. You can use the toolnames filter in the ADK setup. If you only want the agent to use getcontentitem, you explicitly allow just that function.

Feed your Google ADK agents real-time Kontent.ai data. Process massive content repositories using Gemini's million-token context window.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Kontent.ai MCP to Google ADK

Create your Vinkius account to connect Kontent.ai 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.

GDPR Free for Subscribers

Setup Kontent.ai with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Query Content via Google ADK

`search_kontent_ai` lets your Gemini agent execute complex queries against your headless CMS. It pulls the resulting items directly into the context window for immediate analysis. `list_content_items` feeds bulk data to your agent. Since Gemini handles massive token counts, you can dump hundreds of articles into the context and ask the agent to map relationships across your entire library.

Inspect Content Types and Elements

`get_content_type_element` retrieves the exact constraints of a specific field, like the allowed options in a multiple-choice element. Your agent uses this to understand the boundaries of your data structure. `get_content_type` pulls the parent schema. When your agent builds a Vertex AI pipeline, it knows exactly what fields to expect from the CMS payload.

Map Taxonomies with this MCP Server

`get_taxonomy_group` fetches the specific hierarchical tags used in your project. Your agent maps these tags to BigQuery datasets for cross-platform analytics. `list_project_languages` returns the localization options. If you are translating content, the agent checks this list first to ensure the target language actually exists in your Kontent.ai instance.

Setup guide

Set up Kontent.ai 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 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_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Kontent.ai tools via MCP.",
    tools=mcp_tools,
)

Get your connection token →

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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Kontent.ai now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Kontent.ai MCP in Google ADK

Install `google-adk` via pip. Create a `McpToolset` using `StreamableHttpServerParameters` with your Vinkius URL, then pass it to the `LlmAgent` under the `tools` argument.

Yes. You can use the `tool_names` filter in the ADK setup. If you only want the agent to use `get_content_item`, you explicitly allow just that function.

Agents dynamically chain actions. An agent can fetch a taxonomy group, realize it needs more context, and immediately execute a search query without you writing custom orchestration logic.

The ADK processes tool executions sequentially by default. You manage concurrency at the agent level to avoid hitting the standard API limits.

No. The Vinkius infrastructure runs your MCP server in an ephemeral sandbox. Your content types and element definitions are securely fetched and passed directly to your agent over a single authenticated endpoint.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript