How to integrate Datadog MCP with Google ADK

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Introduction

This guide walks you through connecting Datadog to Google ADK using the Composio tool router. By the end, you'll have a working Datadog agent that can create downtime for nightly maintenance window, list all monitors tracking cpu usage, create synthetic api test for login endpoint, get details of production dashboard through natural language commands.

This guide will help you understand how to give your Google ADK agent real control over a Datadog account through Composio's Datadog 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 Datadog account set up and connected to Composio
  • Install the Google ADK and Composio packages
  • Create a Composio Tool Router session for Datadog
  • Build an agent that connects to Datadog through MCP
  • Interact with Datadog 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 Datadog MCP server, and what's possible with it?

The Datadog MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Datadog account. It provides structured and secure access to your monitoring and observability platform, so your agent can perform actions like creating dashboards, managing monitors, scheduling downtimes, and tracking key events on your behalf.

  • Custom dashboard creation and management: Direct your agent to build new dashboards or retrieve detailed information about existing dashboards for unified infrastructure and application monitoring.
  • Monitor setup and deletion: Easily have your agent create new monitors to track critical metrics or remove outdated ones to keep your alerting system relevant.
  • Automated downtime scheduling: Let your agent schedule maintenance windows by creating downtimes that suppress alerts during planned outages or deployments.
  • Event tracking and logging: Ask your agent to create and log significant events—like deployments or configuration changes—so your team always stays informed.
  • Service level objectives and synthetic testing: Instruct your agent to define SLOs or set up synthetic API tests for continuous reliability and performance tracking.

Supported Tools & Triggers

Tools
Create DashboardCreate a dashboard in datadog.
Create downtimeCreates a new downtime in datadog to suppress alerts during maintenance windows or planned outages.
Create eventCreates a new event in datadog.
Create monitorCreates a new datadog monitor to track metrics, logs, or other data sources with configurable alerting thresholds and notifications.
Create SLOCreate a service level objective (slo) in datadog.
Create Synthetic API TestCreate a synthetic api test in datadog.
Create WebhookCreate a webhook in datadog.
Delete DashboardDelete a dashboard in datadog.
Delete monitorDeletes a datadog monitor permanently.
Get DashboardGet a specific dashboard from datadog.
Get monitorRetrieves detailed information about a specific datadog monitor, including its current state, configuration, and any active downtimes.
Get Service DependenciesGet service dependency mapping from datadog apm.
Get Synthetics LocationsTool to retrieve all available public and private locations for synthetic tests in datadog.
Get host tagsRetrieves all tags associated with a specific host in datadog.
Get Trace by IDGet detailed information about a specific trace by its id.
Get usage summaryRetrieves usage summary information from datadog including api calls, hosts, containers, and other billable usage metrics.
List All TagsList all tags from datadog.
List API KeysList api keys in datadog.
List APM ServicesList apm services from datadog.
List AWS IntegrationList aws integrations in datadog.
List dashboardsLists all datadog dashboards with basic information.
List eventsLists events from datadog within a specified time range.
List hostsLists all hosts in your datadog infrastructure with detailed information including metrics, tags, and status.
List IncidentsList incidents from datadog.
List Log IndexesTool to retrieve a list of all log indexes configured in datadog.
List monitorsGet all monitor details.
List RolesList roles from datadog organization.
List service checksLists service checks from datadog.
List SLOsList service level objectives (slos) from datadog.
List Synthetics TestsList synthetics tests from datadog.
List UsersList users from datadog organization.
List WebhooksList webhooks from datadog.
Mute MonitorMute a monitor in datadog.
Query metricsQueries datadog metrics and returns time series data.
Search logsSearches datadog logs with advanced filtering capabilities.
Search Spans AnalyticsSearch and analyze span data with aggregations in datadog.
Search TracesSearch for traces in datadog apm.
Submit metricsSubmits custom metrics to datadog.
Unmute MonitorUnmute a monitor in datadog.
Update DashboardUpdate a dashboard in datadog.
Update host tagsUpdates tags for a specific host in datadog.
Update monitorUpdates an existing datadog monitor with new configuration, thresholds, or notification settings.

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 Datadog 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=["datadog"],
)

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 Datadog 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 Datadog 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 Datadog 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=["datadog"],
        )

        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 Datadog 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 Datadog 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 Datadog with the Google ADK through Composio's MCP Tool Router. Your agent can now interact with Datadog using natural language commands.

Key takeaways:

  • The Tool Router approach dynamically routes requests to the appropriate Datadog 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.

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Mastra AI

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CrewAI

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Use Datadog MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Datadog MCP?

With a standalone Datadog MCP server, the agents and LLMs can only access a fixed set of Datadog tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Datadog 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 Datadog tools.

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

Yes, absolutely. You can configure which Datadog 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 Datadog data and credentials are handled as safely as possible.

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