How to integrate Google cloud vision MCP with Mastra AI

This guide walks you through connecting Google cloud vision to Mastra AI using the Composio tool router. By the end, you'll have a working Google cloud vision agent that can bulk import product images from gcs csv, list all vision ai service locations, create a new product for image recognition through natural language commands. This guide will help you understand how to give your Mastra AI agent real control over a Google cloud vision account through Composio's Google cloud vision MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Google cloud vision logoGoogle cloud vision
Api Key

Google Cloud Vision API adds advanced image analysis—like labeling, OCR, and detection—to apps. It helps you extract structured data and insights from images at scale.

29 Tools

Introduction

This guide walks you through connecting Google cloud vision to Mastra AI using the Composio tool router. By the end, you'll have a working Google cloud vision agent that can bulk import product images from gcs csv, list all vision ai service locations, create a new product for image recognition through natural language commands.

This guide will help you understand how to give your Mastra AI agent real control over a Google cloud vision account through Composio's Google cloud vision MCP server.

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

Also integrate Google cloud vision with

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 Google cloud vision tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Google cloud vision 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 Google cloud vision 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 Google cloud vision MCP server, and what's possible with it?

The Google cloud vision MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Google Cloud Vision account. It provides structured and secure access to your image analysis resources, so your agent can perform actions like registering products, managing reference images, listing endpoints, and automating large-scale image operations on your behalf.

  • Product and reference image management: Easily create new products and add reference images for visual search, enabling your agent to organize and expand your vision datasets effortlessly.
  • Bulk import and product set operations: Let your agent import large numbers of reference images into product sets from Cloud Storage CSV files, streamlining dataset curation at scale.
  • Automated product cleanup and deletion: Direct your agent to purge unused or orphan products from your project, keeping your cloud resources tidy without manual effort.
  • Location and endpoint discovery: Quickly list available Vision AI service locations and existing IndexEndpoints, making it easy for your agent to select optimal regions and manage deployment targets.
  • Vision API operation tracking: Retrieve and review ongoing or past Vision API operations, so your agent can monitor processing jobs and ensure workflow transparency.

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:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript
2

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 Google cloud vision through MCP.
3

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
4

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
5

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
6

Create a Tool Router session for Google cloud vision

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

  const composioMCPUrl = session.mcp.url;
  console.log("Google cloud vision MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "google_cloud_vision" for Google cloud vision access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
7

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 Google cloud vision toolkit
8

Create the Mastra agent

typescript
const agent = new Agent({
    name: "google_cloud_vision-mastra-agent",
    instructions: "You are an AI agent with Google cloud vision 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
9

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: {
        google_cloud_vision: 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 Google cloud vision 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 Google cloud vision 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: ["google_cloud_vision"],
  });

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "google_cloud_vision-mastra-agent",
    instructions: "You are an AI agent with Google cloud vision 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: { google_cloud_vision: 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 Google cloud vision 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
TOOLS

Supported Tools

Every Google cloud vision action and event your agent gets out of the box.

Annotate Files with Vision API

Tool to perform image detection and annotation for batch files in Google Cloud Vision.

Async Batch Annotate Files

Tool to run asynchronous image detection and annotation for a list of generic files (PDF, TIFF, GIF).

Annotate Images

Run image detection and annotation for a batch of images using Google Cloud Vision API.

Annotate Images Async Batch

Tool to run asynchronous image detection and annotation for a batch of images.

Annotate Location Images

Tool to run image detection and annotation for a batch of images scoped to a specific project and location.

Create Vision Product

Creates a new Product resource in Google Cloud Vision Product Search.

Create Product Set

Creates a new ProductSet resource in Google Cloud Vision Product Search.

Create ReferenceImage

Tool to create a ReferenceImage under a product.

Delete Product

Permanently deletes a Product and its associated reference images from Google Cloud Vision API.

Get Product

Tool to get information associated with a Product.

Get Product Set

Tool to get a ProductSet.

Import Product Sets

Asynchronously imports product sets and reference images from a CSV file stored in Google Cloud Storage.

List Vision AI IndexEndpoints

Lists IndexEndpoints in Vertex AI Vision for a given project and location.

List Locations

Tool to list available Vision AI service locations for a project.

List Vision API Operations

Tool to list operations that match the specified filter.

Purge Products

Tool to asynchronously delete products in a ProductSet or orphan products.

Update Product

Tool to update a Product's mutable fields: displayName, description, and productLabels.

Update Product Set

Tool to update a ProductSet resource.

Add Product to ProductSet

Add a Product to a ProductSet in Google Cloud Vision Product Search.

Cancel Vision Operation

Starts asynchronous cancellation of a long-running Vision API operation.

Delete Vision API Operation

Tool to delete a long-running Vision API operation.

Delete Product Set

Tool to permanently delete a ProductSet.

Delete Reference Image

Permanently removes a reference image from a product in Google Cloud Vision Product Search.

Get Vision API Operation

Retrieves the latest state of a long-running Vision API operation.

Get Reference Image

Tool to get information associated with a ReferenceImage.

List Products in ProductSet

Tool to list Products in a specified ProductSet.

List Projects

List Google Cloud projects accessible to the authenticated user via Cloud Resource Manager API.

List Reference Images

Tool to list reference images for a product.

Remove Product from ProductSet

Removes a Product from a specified ProductSet in Google Cloud Vision API.

FAQ

Frequently asked questions

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

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 Google cloud vision tools.

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

Start with Google cloud vision.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Google cloud vision tool your agent needs.Free to start.

Start building