How to integrate Kontent ai MCP with Google ADK

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Introduction

This guide walks you through connecting Kontent ai to Google ADK using the Composio tool router. By the end, you'll have a working Kontent ai agent that can fetch all content items for blog section, get english variant of specific article, list all supported languages in project, retrieve all content type definitions through natural language commands.

This guide will help you understand how to give your Google ADK agent real control over a Kontent ai account through Composio's Kontent ai MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Get a Kontent ai account set up and connected to Composio
  • Install the Google ADK and Composio packages
  • Create a Composio Tool Router session for Kontent ai
  • Build an agent that connects to Kontent ai through MCP
  • Interact with Kontent ai using natural language

What is Google ADK?

Google ADK (Agents Development Kit) is Google's framework for building AI agents powered by Gemini models. It provides tools for creating agents that can use external services through the Model Context Protocol.

Key features include:

  • Gemini Integration: Native support for Google's Gemini models
  • MCP Toolset: Built-in support for Model Context Protocol tools
  • Streamable HTTP: Connect to external services through streamable HTTP
  • CLI and Web UI: Run agents via command line or web interface

What is the Kontent ai MCP server, and what's possible with it?

The Kontent ai MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Kontent ai account. It provides structured and secure access to your headless CMS, so your agent can fetch content items, retrieve language variants, list content types, and manage your content operations seamlessly on your behalf.

  • Fetch specific content items: Instantly retrieve any content item by its identifier to power websites, apps, or previews.
  • Access language variants for localization: Let your agent pull localized versions of any content item, helping you deliver content in multiple languages.
  • List and explore content types: Quickly generate overviews or documentation of your content models by listing all content types in your environment.
  • Retrieve and manage project languages: Effortlessly list all available languages in your Kontent ai project to support localization and translation workflows.
  • Paginated content retrieval for large projects: Use continuation tokens to fetch and navigate through large collections of content items or types without hitting API limits.

Supported Tools & Triggers

Tools
Get Content ItemTool to retrieve a specific content item by its identifier.
Get LanguageTool to retrieve a specific language by its id.
Get Language VariantTool to retrieve a specific language variant of a content item.
List Content ItemsTool to list content items from the delivery api.
List Content TypesTool to list content types within a kontent.
List LanguagesTool to list languages in a kontent.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • A Google API key for Gemini models
  • A Composio account and API key
  • Python 3.9 or later installed
  • Basic familiarity with Python

Getting API Keys for Google and Composio

Google API Key
  • Go to Google AI Studio and create an API key.
  • Copy the key and keep it safe. You will put this in GOOGLE_API_KEY.
Composio API Key and User ID
  • Log in to the Composio dashboard.
  • Go to Settings → API Keys and copy your Composio API key. Use this for COMPOSIO_API_KEY.
  • Decide on a stable user identifier to scope sessions, often your email or a user ID. Use this for COMPOSIO_USER_ID.

Install dependencies

bash
pip install google-adk composio-google python-dotenv

Inside your virtual environment, install the required packages.

What's happening:

  • google-adk is Google's Agents Development Kit
  • composio connects your agent to Kontent ai via MCP
  • composio-google provides the Google ADK provider
  • python-dotenv loads environment variables

Set up ADK project

bash
adk create my_agent

Set up a new Google ADK project.

What's happening:

  • This creates an agent folder with a root agent file and .env file

Set environment variables

bash
GOOGLE_API_KEY=your-google-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id-or-email

Save all your credentials in the .env file.

What's happening:

  • GOOGLE_API_KEY authenticates with Google's Gemini models
  • COMPOSIO_API_KEY authenticates with Composio
  • COMPOSIO_USER_ID identifies the user for session management

Import modules and validate environment

python
import os
import warnings

from composio import Composio
from composio_google import GoogleProvider
from dotenv import load_dotenv
from google.adk.agents.llm_agent import Agent
from google.adk.tools.mcp_tool.mcp_session_manager import StreamableHTTPConnectionParams
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset

load_dotenv()

warnings.filterwarnings("ignore", message=".*BaseAuthenticatedTool.*")

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")
What's happening:
  • os reads environment variables
  • Composio is the main Composio SDK client
  • GoogleProvider declares that you are using Google ADK as the agent runtime
  • Agent is the Google ADK LLM agent class
  • McpToolset lets the ADK agent call MCP tools over HTTP

Create Composio client and Tool Router session

python
print("Initializing Composio client...")
composio_client = Composio(api_key=COMPOSIO_API_KEY, provider=GoogleProvider())

print("Creating Composio session...")
composio_session = composio_client.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["kontent_ai"],
)

COMPOSIO_MCP_URL = composio_session.mcp.url
print(f"Composio MCP HTTP URL: {COMPOSIO_MCP_URL}")
What's happening:
  • Authenticates to Composio with your API key
  • Declares Google ADK as the provider
  • Spins up a short-lived MCP endpoint for your user and selected toolkit
  • Stores the MCP HTTP URL for the ADK MCP integration

Set up the McpToolset and create the Agent

python
print("Creating Composio toolset for the agent...")
composio_toolset = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url=COMPOSIO_MCP_URL,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )
)

root_agent = Agent(
    model="gemini-2.5-pro",
    name="composio_agent",
    description="An agent that uses Kontent ai tools to perform actions.",
    instruction=(
        "You are a helpful assistant connected to Composio. "
        "You have the following tools available: "
        "COMPOSIO_SEARCH_TOOLS, COMPOSIO_MULTI_EXECUTE_TOOL, "
        "COMPOSIO_MANAGE_CONNECTIONS, COMPOSIO_REMOTE_BASH_TOOL, COMPOSIO_REMOTE_WORKBENCH. "
        "Use these tools to help users with Kontent ai operations."
    ),
    tools=[composio_toolset],
)

print("\nAgent setup complete. You can now run this agent directly ;)")
What's happening:
  • Connects the ADK agent to the Composio MCP endpoint through McpToolset
  • Uses Gemini as the model powering the agent
  • Lists exact tool names in instruction to reduce misnamed tool calls

Run the agent

bash
# Run in CLI mode
adk run my_agent

# Or run in web UI mode
adk web
Execute the agent from the project root. The web command opens a web portal where you can chat with the agent. What's happening:
  • adk run runs the agent in CLI mode
  • adk web opens a web UI for interactive testing

Complete Code

Here's the complete code to get you started with Kontent ai and Google ADK:

python
import os
import warnings

from composio import Composio
from composio_google import GoogleProvider
from dotenv import load_dotenv
from google.adk.agents.llm_agent import Agent
from google.adk.tools.mcp_tool.mcp_session_manager import StreamableHTTPConnectionParams
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset

def main():
    try:
        load_dotenv()

        warnings.filterwarnings("ignore", message=".*BaseAuthenticatedTool.*")

        GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
        COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
        COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

        if not GOOGLE_API_KEY:
            raise ValueError("GOOGLE_API_KEY is not set in the environment.")
        if not COMPOSIO_API_KEY:
            raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
        if not COMPOSIO_USER_ID:
            raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

        print("Initializing Composio client...")
        composio_client = Composio(api_key=COMPOSIO_API_KEY, provider=GoogleProvider())

        print("Creating Composio session...")
        composio_session = composio_client.create(
            user_id=COMPOSIO_USER_ID,
            toolkits=["kontent_ai"],
        )

        COMPOSIO_MCP_URL = composio_session.mcp.url
        print(f"Composio MCP HTTP URL: {COMPOSIO_MCP_URL}")

        print("Creating Composio toolset for the agent...")
        composio_toolset = McpToolset(
            connection_params=StreamableHTTPConnectionParams(
                url=COMPOSIO_MCP_URL,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
            )
        )

        root_agent = Agent(
            model="gemini-2.5-pro",
            name="composio_agent",
            description="An agent that uses Kontent ai tools to perform actions.",
            instruction=(
                "You are a helpful assistant connected to Composio. "
                "You have the following tools available: "
                "COMPOSIO_SEARCH_TOOLS, COMPOSIO_MULTI_EXECUTE_TOOL, "
                "COMPOSIO_MANAGE_CONNECTIONS, COMPOSIO_REMOTE_BASH_TOOL, COMPOSIO_REMOTE_WORKBENCH. "
                "Use these tools to help users with Kontent ai operations."
            ),
            tools=[composio_toolset],
        )

        print("\nAgent setup complete. You can now run this agent directly ;)")

    except Exception as e:
        print(f"\nAn error occurred during agent setup: {e}")

if __name__ == "__main__":
    main()

Conclusion

You've successfully integrated Kontent ai with the Google ADK through Composio's MCP Tool Router. Your agent can now interact with Kontent ai using natural language commands.

Key takeaways:

  • The Tool Router approach dynamically routes requests to the appropriate Kontent ai tools
  • Environment variables keep your credentials secure and separate from code
  • Clear agent instructions reduce tool calling errors
  • The ADK web UI provides an interactive interface for testing and development

You can extend this setup by adding more toolkits to the toolkits array in your session configuration.

How to build Kontent ai MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Kontent ai MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Kontent ai MCP with Claude Agent SDK

LangChain

LangChain

Use Kontent ai MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Kontent ai MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Kontent ai MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Kontent ai MCP with LlamaIndex

CrewAI

CrewAI

Use Kontent ai MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Kontent ai MCP?

With a standalone Kontent ai MCP server, the agents and LLMs can only access a fixed set of Kontent ai tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Kontent ai and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with Google ADK?

Yes, you can. Google ADK fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Kontent ai tools.

Can I manage the permissions and scopes for Kontent ai while using Tool Router?

Yes, absolutely. You can configure which Kontent ai scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Kontent ai data and credentials are handled as safely as possible.

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