How to integrate Docker hub MCP with Mastra AI

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Introduction

This guide walks you through connecting Docker hub to Mastra AI using the Composio tool router. By the end, you'll have a working Docker hub agent that can create a new docker hub repository, add a member to my docker organization, delete an old image from a repository, set up a webhook for repository updates through natural language commands.

This guide will help you understand how to give your Mastra AI agent real control over a Docker hub account through Composio's Docker hub 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:
  • Set up your environment so Mastra, OpenAI, and Composio work together
  • Create a Tool Router session in Composio that exposes Docker hub tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Docker hub tool definitions and attach them as a toolset
  • Build a Mastra agent that can reason, call tools, and return structured results
  • Run an interactive CLI where you can chat with your Docker hub agent

What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.

Key features include:

  • MCP Client: Built-in support for Model Context Protocol servers
  • Toolsets: Organize tools into logical groups
  • Step Callbacks: Monitor and debug agent execution
  • OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

What is the Docker hub MCP server, and what's possible with it?

The Docker hub MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Docker Hub account. It provides structured and secure access to your container repositories and organizations, so your agent can perform actions like creating repositories, managing organization members, deleting images, setting up webhooks, and cleaning up tags on your behalf.

  • Repository and image management: Let your agent create new Docker Hub repositories, delete existing ones, and remove specific images or tags as needed.
  • Organization and team automation: Easily add members to organizations, create new Docker Hub organizations, or delete organizations and teams directly from your workflows.
  • Webhook configuration: Set up or remove repository webhooks to automate external integrations and keep your CI/CD pipelines in sync.
  • Tag and resource cleanup: Direct your agent to delete outdated tags or unused resources, helping you maintain a tidy container registry.
  • Secure role management: Invite users with specific roles to your organizations, ensuring the right access for collaborators and teams.

Supported Tools & Triggers

Tools
Add Organization MemberTool to send an invitation for a user to join a Docker Hub organization.
Create Docker Hub OrganizationTool to create a Docker Hub organization.
Create Docker Hub RepositoryTool to create a Docker Hub repository under a namespace.
Create Docker Hub WebhookTool to create a webhook on a Docker Hub repository.
Delete Repository ImageTool to delete a specific image within a Docker Hub repository.
Delete Docker Hub OrganizationTool to delete a specific Docker Hub organization.
Delete Docker Hub RepositoryTool to delete a specific Docker Hub repository.
Delete Repository TagTool to delete a specific tag from a Docker Hub repository.
Delete Docker Hub TeamTool to delete a specific team from an organization.
Delete Docker Hub repository webhookTool to delete a specific webhook from a repository.
Get Docker Hub ImageTool to retrieve detailed information about a specific image within a Docker Hub repository.
Get Organization DetailsTool to retrieve details of a specific organization namespace.
Get Docker Hub RepositoryTool to retrieve details of a specific Docker Hub repository.
Get Docker Hub TagTool to retrieve details of a specific Docker Hub repository tag.
Get Docker Hub TeamTool to retrieve a specific Docker Hub team.
Get Docker Hub WebhookTool to retrieve details of a specific Docker Hub webhook.
List Repository ImagesTool to list image variants for a specific Docker Hub repository.
List Docker Hub OrganizationsTool to list organizations (namespaces) for the authenticated user.
List Docker Hub Organization MembersTool to list members of a Docker Hub organization.
List Docker Hub RepositoriesTool to list repositories under a namespace.
List Repository TagsTool to list tags for a Docker Hub repository.
List Team MembersTool to list members of a Docker Hub team.
List Organization TeamsTool to list teams in a specific organization.
List Docker Hub repository webhooksTool to list webhooks for a Docker Hub repository.
Remove Organization MemberTool to remove a user from a Docker Hub organization.
Remove Team MemberTool to remove a user from a Docker Hub team.

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:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key.
  • You need credits or a connected billing setup to use the models.
  • Store the key somewhere safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Go to Settings and copy your API key.
  • This key lets your Mastra agent talk to Composio and reach Docker hub through MCP.

Install dependencies

bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv

Install the required packages.

What's happening:

  • @composio/core is the Composio SDK for creating MCP sessions
  • @mastra/core provides the Agent class
  • @mastra/mcp is Mastra's MCP client
  • @ai-sdk/openai is the model wrapper for OpenAI
  • dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio
  • COMPOSIO_USER_ID tells Composio which user this session belongs to
  • OPENAI_API_KEY lets the Mastra agent call OpenAI models

Import libraries and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey as string,
});
What's happening:
  • dotenv/config auto loads your .env so process.env.* is available
  • openai gives you a Mastra compatible model wrapper
  • Agent is the Mastra agent that will call tools and produce answers
  • MCPClient connects Mastra to your Composio MCP server
  • Composio is used to create a Tool Router session

Create a Tool Router session for Docker hub

typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["docker_hub"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Docker hub MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "docker_hub" for Docker hub access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to

Configure Mastra MCP client and fetch tools

typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
What's happening:
  • MCPClient takes an id for this client and a list of MCP servers
  • The headers property includes the x-api-key for authentication
  • getTools fetches the tool definitions exposed by the Docker hub toolkit

Create the Mastra agent

typescript
const agent = new Agent({
    name: "docker_hub-mastra-agent",
    instructions: "You are an AI agent with Docker hub tools via Composio.",
    model: "openai/gpt-5",
  });
What's happening:
  • Agent is the core Mastra agent
  • name is just an identifier for logging and debugging
  • instructions guide the agent to use tools instead of only answering in natural language
  • model uses openai("gpt-5") to configure the underlying LLM

Set up interactive chat interface

typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\n");

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

rl.prompt();

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        docker_hub: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • messages keeps the full conversation history in Mastra's expected format
  • agent.generate runs the agent with conversation history and Docker hub toolsets
  • maxSteps limits how many tool calls the agent can take in a single run
  • onStepFinish is a hook that prints intermediate steps for debugging

Complete Code

Here's the complete code to get you started with Docker hub and Mastra AI:

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({ apiKey: composioAPIKey as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["docker_hub"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      docker_hub: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "docker_hub-mastra-agent",
    instructions: "You are an AI agent with Docker hub tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

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

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { docker_hub: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();

Conclusion

You've built a Mastra AI agent that can interact with Docker hub through Composio's Tool Router. You can extend this further by:
  • Adding other toolkits like Gmail, Slack, or GitHub
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows

How to build Docker hub MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Docker hub MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Docker hub MCP with Claude Agent SDK

Google ADK

Google ADK

Use Docker hub MCP with Google ADK

LangChain

LangChain

Use Docker hub MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Docker hub MCP with Vercel AI SDK

LlamaIndex

LlamaIndex

Use Docker hub MCP with LlamaIndex

CrewAI

CrewAI

Use Docker hub MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Docker hub MCP?

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

Can I use Tool Router MCP with Mastra AI?

Yes, you can. Mastra AI 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 Docker hub tools.

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

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

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