How to integrate Scale ai MCP with Claude Agent SDK

This guide walks you through connecting Scale ai to the Claude Agent SDK 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 Claude Agent SDK 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.

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Scale ai provides machine learning data labeling and annotation services. It enables teams to train AI models with high-quality, human-labeled data at scale.

41 Tools

Introduction

This guide walks you through connecting Scale ai to the Claude Agent SDK 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 Claude Agent SDK 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.

Also integrate Scale ai with

OpenAI Agents SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your Claude/Anthropic and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Scale ai
  • Configure an AI agent that can use Scale ai as a tool
  • Run a live chat session where you can ask the agent to perform Scale ai operations

What is Claude Agent SDK?

The Claude Agent SDK is Anthropic's official framework for building AI agents powered by Claude. It provides a streamlined interface for creating agents with MCP tool support and conversation management.

Key features include:

  • Native MCP Support: Built-in support for Model Context Protocol servers
  • Permission Modes: Control tool execution permissions
  • Streaming Responses: Real-time response streaming for interactive applications
  • Context Manager: Clean async context management for sessions

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.

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

What is Composio SDK?

Composio's Composio SDK 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 Composio SDK

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

How the Composio SDK works

The Composio SDK 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

Step by step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Composio API Key and Claude/Anthropic API Key
  • Primary know-how of Claude Agents SDK
  • A Scale ai account
  • Some knowledge of Python
2

Getting API Keys for Claude/Anthropic and Composio

Claude/Anthropic API Key
  • Go to the Anthropic Console and create an API key. You'll need credits to use the models.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

npm install @anthropic-ai/claude-agent-sdk @composio/core dotenv

Install the Composio SDK and the Claude Agents SDK.

What's happening:

  • @composio/core provides Composio integration for Anthropic
  • @anthropic-ai/claude-agent-sdk is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
ANTHROPIC_API_KEY=your_anthropic_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID identifies the user for session management
  • ANTHROPIC_API_KEY authenticates with Anthropic/Claude
5

Import dependencies

import 'dotenv/config';
import readline from 'node:readline';
import { Composio } from '@composio/core';
import { query, type Options } from "@anthropic-ai/claude-agent-sdk";

dotenv.config();
What's happening:
  • We're importing all necessary libraries including the Claude Agent SDK and Composio
  • The dotenv.config() function loads environment variables from your .env file
  • This setup prepares the foundation for connecting Claude with Scale ai functionality
6

Create a Composio instance and Tool Router session

async function chat() {
  const { COMPOSIO_API_KEY, USER_ID } = process.env;
  if (!COMPOSIO_API_KEY || !USER_ID) {
    throw new Error('COMPOSIO_API_KEY and USER_ID required in .env');
  }

  const composio = new Composio({ apiKey: COMPOSIO_API_KEY });

  // Create Tool Router session for Scale ai
  const session = await composio.create(USER_ID, {
    toolkits: ['scale_ai'],
  });
  const mcpUrl = session?.mcp.url;
What's happening:
  • The function checks for the required COMPOSIO_API_KEY environment variable
  • We're creating a Composio instance using our API key
  • The create method creates a Tool Router session for Scale ai
  • The returned url is the MCP server URL that your agent will use
7

Configure Claude Agent with MCP

const options: Options = {
  permissionMode: 'bypassPermissions',
  mcpServers: {
    composio: {
      type: 'http',
      url: mcpUrl,
      headers: { 'x-api-key': COMPOSIO_API_KEY }
    }
  },
  systemPrompt: 'You are a helpful assistant with access to Scale ai tools via Composio.',
  maxTurns: 10,
};
What's happening:
  • We're configuring the Claude Agent options with the MCP server URL
  • permissionMode: 'bypassPermissions' allows the agent to execute operations without asking for permission each time
  • The system prompt instructs the agent that it has access to Scale ai
  • maxTurns: 10 limits the conversation length to prevent excessive API usage
8

Create client and start chat loop

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
  });

  console.log('\nChat started. Type "exit" to quit.\n');

  let isProcessing = false;

  async function ask(prompt: string) {
    isProcessing = true;
    rl.pause();

    process.stdout.write('Claude is thinking...');
    const stream = query({ prompt, options });

    let firstChunk = true;
    for await (const msg of stream) {
      const content = (msg as any).message?.content || (msg as any).content;
      if (Array.isArray(content)) {
        for (const block of content) {
          if (block.type === 'text' && block.text) {
            if (firstChunk) {
              process.stdout.write('\r\x1b[K');
              process.stdout.write('Claude: ');
              firstChunk = false;
            }
            process.stdout.write(block.text);
          }
        }
      }
    }
    process.stdout.write('\n\n');

    isProcessing = false;
    rl.resume();
    rl.prompt();
  }

  rl.on('line', async (line) => {
    if (isProcessing) return;

    const input = line.trim();
    if (input === 'exit') {
      rl.close();
      process.exit(0);
    }
    if (input) await ask(input);
    else rl.prompt();
  });

  await ask('What can you help me with?');
}
What's happening:
  • The readline interface is created to handle user input and output
  • The query function is used to send the user's input to the agent
  • The chat loop continues until the user types 'exit' or 'quit'
9

Run the application

try {
  await chat();
} catch (error) {
  console.error(error);
  process.exit(1);
}
What's happening:
  • The chat function is the entry point for the application
  • The try-catch block is used to handle any errors that occur

Complete Code

Here's the complete code to get you started with Scale ai and Claude Agent SDK:

import 'dotenv/config';
import readline from 'node:readline';
import { Composio } from '@composio/core';
import { query, type Options } from "@anthropic-ai/claude-agent-sdk";

async function chat() {
  const { COMPOSIO_API_KEY, USER_ID } = process.env;
  if (!COMPOSIO_API_KEY || !USER_ID) {
    throw new Error('COMPOSIO_API_KEY and USER_ID required in .env');
  }

  const composio = new Composio({ apiKey: COMPOSIO_API_KEY });
  const session = await composio.create(USER_ID, {
    toolkits: ['scale_ai']
  });
  const mcp_url = session?.mcp.url;

  const options: Options = {
    permissionMode: 'bypassPermissions',
    mcpServers: {
      composio: {
        type: 'http',
        url: mcp_url,
        headers: { 'x-api-key': COMPOSIO_API_KEY }
      }
    },
    systemPrompt: 'You are a helpful assistant with access to Scale ai tools via Composio.',
    maxTurns: 10,
  };

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
  });

  console.log('\nChat started. Type "exit" to quit.\n');

  let isProcessing = false;

  async function ask(prompt: string) {
    isProcessing = true;
    rl.pause();

    process.stdout.write('Claude is thinking...');
    const stream = query({ prompt, options });

    let firstChunk = true;
    for await (const msg of stream) {
      const content = (msg as any).message?.content || (msg as any).content;
      if (Array.isArray(content)) {
        for (const block of content) {
          if (block.type === 'text' && block.text) {
            if (firstChunk) {
              process.stdout.write('\r\x1b[K');
              process.stdout.write('Claude: ');
              firstChunk = false;
            }
            process.stdout.write(block.text);
          }
        }
      }
    }
    process.stdout.write('\n\n');

    isProcessing = false;
    rl.resume();
    rl.prompt();
  }

  rl.on('line', async (line) => {
    if (isProcessing) return;

    const input = line.trim();
    if (input === 'exit') {
      rl.close();
      process.exit(0);
    }
    if (input) await ask(input);
    else rl.prompt();
  });

  await ask('What can you help me with?');
}

try {
  await chat();
} catch (error) {
  console.error(error);
  process.exit(1);
}

Conclusion

You've successfully built a Claude Agent SDK agent that can interact with Scale ai through Composio's Tool Router.

Key features:

  • Native MCP support through Claude's agent framework
  • Streaming responses for real-time interaction
  • Permission bypass for smooth automated workflows
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.
TOOLS

Supported Tools

Every Scale ai action and event your agent gets out of the box.

Add Studio Assignments

Tool to add project assignments to team members in Scale AI Studio.

Add Task Tags

Tool to add tags to an existing task.

Create Batch

Tool to create a new batch within a project.

Create Document Transcription Task

Tool to create a document transcription task where workers transcribe and annotate information from single or multi-page documents.

Create Image Annotation Task

Tool to create an image annotation task where annotators label images with vector geometric shapes (box, polygon, line, point, cuboid, ellipse).

Create Lidar Annotation Task

Tool to create a lidar annotation task where annotators mark objects with 3D cuboids in 3D space.

Create LiDAR Segmentation Task

Tool to create a LiDAR segmentation task where annotators assign semantic class labels to individual LiDAR points.

Create Named Entity Recognition Task

Tool to create a named entity recognition task for labelers to highlight text entity mentions.

Create Segmentation Annotation Task

Tool to create a segmentation task where annotators classify pixels in an image according to provided labels.

Create Text Collection Task

Tool to create a textcollection task for collecting information from attachments and/or web sources.

Create Video Annotation Task

Tool to create a video annotation task where annotators draw geometric shapes around specified objects across video frames.

Create Video Playback Annotation Task

Tool to create a video playback annotation task where annotators draw shapes around specified objects in video files.

Delete Task Tags

Tool to remove specified tags from a Scale AI task.

Delete Task Unique ID

Tool to remove the unique identifier from a task.

Finalize Batch

Tool to finalize a batch so its tasks can be worked on.

Get Assets

Tool to retrieve file assets with filtering capabilities by project and metadata.

Get Batch

Tool to retrieve the details of a batch with the specified name.

Get Batch Status

Tool to retrieve the current status of a batch and task completion counts.

Get Fixless Audits

Tool to retrieve fixless audits by task ID or audit ID.

Get Project

Tool to retrieve details about a specific Scale AI project using its unique identifier.

Get Quality Labelers

Tool to retrieve training attempts matching provided filter parameters.

Get Studio Assignments

Tool to retrieve current project assignments of all active team users in Scale AI Studio.

Get Studio Batches

Tool to retrieve basic information about all pending batches in Studio.

Get Task

Tool to retrieve detailed information about a specific task in Scale AI.

Get Teams

Tool to retrieve basic information about all team members associated with the account.

Get Task by ID

Tool to retrieve detailed information about a specific task using its task ID.

Get Secure Task Response URL

Tool to retrieve secure authenticated task response data.

Import File

Tool to import files from an external URL endpoint into Scale's system rather than uploading directly from local storage.

Invite Team Member

Tool to invite users by email to team with specified role.

List Batches

Tool to retrieve all batches in descending order by creation date.

List Projects

Tool to retrieve information for all projects in the Scale AI account with optional archived filtering.

List Tasks

Tool to retrieve a paginated list of tasks in descending order by creation time.

Re-send Task Callback

Tool to re-send a callback for a completed or errored task to the callback_url.

Remove Studio Assignments

Tool to unassign projects from specified team members in Scale AI Studio.

Reset Batch Priorities

Tool to restore batch priority order to default order (calibration batches first, then sorted by creation date).

Set Batch Priorities

Tool to modify batch priority order in Scale AI Studio.

Set Project Ontology

Tool to set ontologies on a Scale AI project.

Set Project Parameters

Tool to set default parameters for tasks created under a project.

Set Task Metadata

Tool to set key-value metadata on an existing Scale AI task.

Update Task Unique ID

Tool to update or assign a unique identifier to a task.

Upload File

Tool to upload a local file to Scale's servers with a maximum size limit of 80 MB per file.

FRAMEWORKS

How to build Scale ai MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Scale ai MCP with OpenAI Agents SDK

Claude Code logo

Claude Code

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Claude Cowork logo

Claude Cowork

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Codex logo

Codex

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OpenClaw logo

OpenClaw

Use Scale ai MCP with OpenClaw

Hermes logo

Hermes

Use Scale ai MCP with Hermes

CLI logo

CLI

Use Scale ai MCP with CLI

Google ADK logo

Google ADK

Use Scale ai MCP with Google ADK

LangChain logo

LangChain

Use Scale ai MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Scale ai MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Scale ai MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Scale ai MCP with LlamaIndex

CrewAI logo

CrewAI

Use Scale ai MCP with CrewAI

FAQ

Frequently asked questions

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.

Yes, you can. Claude Agent SDK 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.

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.

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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A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

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We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

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CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

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Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

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With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

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