How to integrate Scale ai MCP with Google ADK

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Introduction

This guide walks you through connecting Scale ai to Google ADK using the Composio tool router. By the end, you'll have a working Scale ai agent that can create image labeling task for dataset 'road-signs', list completed annotation tasks for project, fetch results of data labeling job through natural language commands.

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

The Scale 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 Scale ai account. It provides structured and secure access so your agent can perform Scale ai operations on your behalf.

Supported Tools & Triggers

Tools
Add Studio AssignmentsTool to add project assignments to team members in Scale AI Studio.
Add Task TagsTool to add tags to an existing task.
Create BatchTool to create a new batch within a project.
Create Document Transcription TaskTool to create a document transcription task where workers transcribe and annotate information from single or multi-page documents.
Create Image Annotation TaskTool to create an image annotation task where annotators label images with vector geometric shapes (box, polygon, line, point, cuboid, ellipse).
Create Lidar Annotation TaskTool to create a lidar annotation task where annotators mark objects with 3D cuboids in 3D space.
Create LiDAR Segmentation TaskTool to create a LiDAR segmentation task where annotators assign semantic class labels to individual LiDAR points.
Create Named Entity Recognition TaskTool to create a named entity recognition task for labelers to highlight text entity mentions.
Create Segmentation Annotation TaskTool to create a segmentation task where annotators classify pixels in an image according to provided labels.
Create Text Collection TaskTool to create a textcollection task for collecting information from attachments and/or web sources.
Create Video Annotation TaskTool to create a video annotation task where annotators draw geometric shapes around specified objects across video frames.
Create Video Playback Annotation TaskTool to create a video playback annotation task where annotators draw shapes around specified objects in video files.
Delete Task TagsTool to remove specified tags from a Scale AI task.
Delete Task Unique IDTool to remove the unique identifier from a task.
Finalize BatchTool to finalize a batch so its tasks can be worked on.
Get AssetsTool to retrieve file assets with filtering capabilities by project and metadata.
Get BatchTool to retrieve the details of a batch with the specified name.
Get Batch StatusTool to retrieve the current status of a batch and task completion counts.
Get Fixless AuditsTool to retrieve fixless audits by task ID or audit ID.
Get ProjectTool to retrieve details about a specific Scale AI project using its unique identifier.
Get Quality LabelersTool to retrieve training attempts matching provided filter parameters.
Get Studio AssignmentsTool to retrieve current project assignments of all active team users in Scale AI Studio.
Get Studio BatchesTool to retrieve basic information about all pending batches in Studio.
Get TaskTool to retrieve detailed information about a specific task in Scale AI.
Get TeamsTool to retrieve basic information about all team members associated with the account.
Get Task by IDTool to retrieve detailed information about a specific task using its task ID.
Get Secure Task Response URLTool to retrieve secure authenticated task response data.
Import FileTool to import files from an external URL endpoint into Scale's system rather than uploading directly from local storage.
Invite Team MemberTool to invite users by email to team with specified role.
List BatchesTool to retrieve all batches in descending order by creation date.
List ProjectsTool to retrieve information for all projects in the Scale AI account with optional archived filtering.
List TasksTool to retrieve a paginated list of tasks in descending order by creation time.
Re-send Task CallbackTool to re-send a callback for a completed or errored task to the callback_url.
Remove Studio AssignmentsTool to unassign projects from specified team members in Scale AI Studio.
Reset Batch PrioritiesTool to restore batch priority order to default order (calibration batches first, then sorted by creation date).
Set Batch PrioritiesTool to modify batch priority order in Scale AI Studio.
Set Project OntologyTool to set ontologies on a Scale AI project.
Set Project ParametersTool to set default parameters for tasks created under a project.
Set Task MetadataTool to set key-value metadata on an existing Scale AI task.
Update Task Unique IDTool to update or assign a unique identifier to a task.
Upload FileTool to upload a local file to Scale's servers with a maximum size limit of 80 MB per file.

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 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 Scale ai via MCP
  • 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 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
composio_client = Composio(api_key=COMPOSIO_API_KEY)

composio_session = composio_client.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["scale_ai"],
)

COMPOSIO_MCP_URL = composio_session.mcp.url,
print(f"Composio MCP 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
composio_toolset = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url=COMPOSIO_MCP_URL,
        headers={"x-api-key": COMPOSIO_API_KEY}
    )
)

root_agent = Agent(
    model="gemini-2.5-flash",
    name="composio_agent",
    description="An agent that uses Composio 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 Scale 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 Scale 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

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.")

composio_client = Composio(api_key=COMPOSIO_API_KEY, provider=GoogleProvider())

composio_session = composio_client.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["scale_ai"],
)

COMPOSIO_MCP_URL = composio_session.mcp.url


composio_toolset = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url=COMPOSIO_MCP_URL,
        headers={"x-api-key": COMPOSIO_API_KEY}
    )
)

root_agent = Agent(
    model="gemini-2.5-flash",
    name="composio_agent",
    description="An agent that uses Composio 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 Scale ai operations."
    ),  
    tools=[composio_toolset],
)

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

Conclusion

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

Key takeaways:

  • The Tool Router approach dynamically routes requests to the appropriate Scale 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 Scale ai MCP Agent with another framework

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OpenAI Agents SDK

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Claude Agent SDK

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Vercel AI SDK

Vercel AI SDK

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Mastra AI

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LlamaIndex

LlamaIndex

Use Scale ai MCP with LlamaIndex

CrewAI

CrewAI

Use Scale ai MCP with CrewAI

Claude Code

Claude Code

Use Scale ai MCP with Claude Code

Codex

Codex

Use Scale ai MCP with Codex

FAQ

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

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

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

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

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