How to integrate Google cloud vision MCP with Pydantic AI

This guide walks you through connecting Google cloud vision to Pydantic 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 Pydantic 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.

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Google 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.

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Introduction

This guide will help you understand how to give your Pydantic 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

ChatGPT OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenCode Cursor VS Code OpenClaw Hermes CLI Google ADK LangChain Vercel AI SDK Mastra AI LlamaIndex CrewAI

TL;DR

Here's what you'll learn:

How to set up your Composio API key and User ID
How to create a Composio Tool Router session for Google cloud vision
How to attach an MCP Server to a Pydantic AI agent
How to stream responses and maintain chat history
How to build a simple REPL-style chat interface to test your Google cloud vision workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

Type Safety: Built on Pydantic for automatic data validation
MCP Support: Native support for Model Context Protocol servers
Streaming: Built-in support for streaming responses
Async First: Designed for async/await patterns

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:

Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS

Prerequisites

Before starting, make sure you have:

Python 3.9 or higher
A Composio account with an active API key
Basic familiarity with Python and async programming

Getting API Keys for OpenAI and Composio

OpenAI API Key

Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
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.

Install dependencies

bash

pip install composio pydantic-ai python-dotenv

Install the required libraries.

What's happening:

composio connects your agent to external SaaS tools like Google cloud vision
pydantic-ai lets you create structured AI agents with tool support
python-dotenv loads your environment variables securely from a .env file

Set up environment variables

bash

COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

COMPOSIO_API_KEY authenticates your agent to Composio's API
USER_ID associates your session with your account for secure tool access
OPENAI_API_KEY to access OpenAI LLMs

Import dependencies

python

import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

What's happening:

We load environment variables and import required modules
Composio manages connections to Google cloud vision
MCPServerStreamableHTTP connects to the Google cloud vision MCP server endpoint
Agent from Pydantic AI lets you define and run the AI assistant

Create a Tool Router Session

python

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Google cloud vision
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["google_cloud_vision"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

What's happening:

We're creating a Tool Router session that gives your agent access to Google cloud vision tools
The create method takes the user ID and specifies which toolkits should be available
The returned session.mcp.url is the MCP server URL that your agent will use

Initialize the Pydantic AI Agent

python

# Attach the MCP server to a Pydantic AI Agent
google_cloud_vision_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[google_cloud_vision_mcp],
    instructions=(
        "You are a Google cloud vision assistant. Use Google cloud vision tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)

What's happening:

The MCP client connects to the Google cloud vision endpoint
The agent uses GPT-5 to interpret user commands and perform Google cloud vision operations
The instructions field defines the agent's role and behavior

Build the chat interface

python

# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Google cloud vision.\n")

while True:
    user_input = input("You: ").strip()
    if user_input.lower() in {"exit", "quit", "bye"}:
        print("\nGoodbye!")
        break
    if not user_input:
        continue

    print("\nAgent is thinking...\n", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()

What's happening:

The agent reads input from the terminal and streams its response
Google cloud vision API calls happen automatically under the hood
The model keeps conversation history to maintain context across turns

Run the application

python

if __name__ == "__main__":
    asyncio.run(main())

What's happening:

The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with Google cloud vision and Pydantic AI:

python

import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Google cloud vision
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["google_cloud_vision"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    google_cloud_vision_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[google_cloud_vision_mcp],
        instructions=(
            "You are a Google cloud vision assistant. Use Google cloud vision tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Google cloud vision.\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "bye"}:
            print("\nGoodbye!")
            break
        if not user_input:
            continue

        print("\nAgent is thinking...\n", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with Google cloud vision through Composio's Tool Router. With this setup, your agent can perform real Google cloud vision actions through natural language. You can extend this further by:

Adding other toolkits like Gmail, HubSpot, or Salesforce
Building a web-based chat interface around this agent
Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Google cloud vision for workflow automation)

This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

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.

FRAMEWORKS

How to build Google cloud vision MCP Agent with another framework

ChatGPT

Use Google cloud vision MCP with ChatGPT

OpenAI Agents SDK

Use Google cloud vision MCP with OpenAI Agents SDK

Claude Agent SDK

Use Google cloud vision MCP with Claude Agent SDK

Claude Code

Use Google cloud vision MCP with Claude Code

Claude Cowork

Use Google cloud vision MCP with Claude Cowork

Codex

Use Google cloud vision MCP with Codex

Cursor

Use Google cloud vision MCP with Cursor

OpenClaw

Use Google cloud vision MCP with OpenClaw

Hermes

Use Google cloud vision MCP with Hermes

CLI

Use Google cloud vision MCP with CLI

Google ADK

Use Google cloud vision MCP with Google ADK

LangChain

Use Google cloud vision MCP with LangChain

Vercel AI SDK

Use Google cloud vision MCP with Vercel AI SDK

Mastra AI

Use Google cloud vision MCP with Mastra AI

LlamaIndex

Use Google cloud vision MCP with LlamaIndex

CrewAI

Use Google cloud vision MCP with CrewAI

OpenCode

Use Google cloud vision MCP with OpenCode

VS Code

Use Google cloud vision MCP with VS Code

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Composio

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Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed.

Composio search

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Composio search is a unified web search toolkit spanning travel, e-commerce, news, financial markets, images, and more. It lets you and your apps tap into up-to-date web data from a single, easy-to-integrate service.

Perplexityai

Api Key

Perplexityai delivers natural, conversational AI models for generating human-like text. Instantly get context-aware, high-quality responses for chat, search, or complex workflows.

Browser tool

No Auth

Browser tool is a virtual browser integration that lets AI agents interact with the web programmatically. It enables automated browsing, scraping, and action-taking from any AI workflow.

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. Pydantic 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.

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Customer stories

Teams ship real agents on Composio

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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati

Co-founder, Slashy

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.

Abhi Arya

Co-founder, Opennote

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.

Nirman Dave

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.

Ryan Yu

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.

Tomisin Jenrola

Founder & CEO, SwarmZero

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.

Jerome Leclanche

Co-Founder, Ingram Technologies

How to integrate Google cloud vision MCP with Pydantic AI

Connect Google cloud vision without auth hassles

Introduction

Also integrate Google cloud vision with

TL;DR

What is Pydantic AI?

What is the Google cloud vision MCP server, and what's possible with it?

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

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import dependencies

Create a Tool Router Session

Initialize the Pydantic AI Agent

Build the chat interface

Run the application

Complete Code

Conclusion

Supported Tools

How to build Google cloud vision MCP Agent with another framework

ChatGPT

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

Cursor

OpenClaw

Hermes

CLI

Google ADK

LangChain

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

OpenCode

VS Code

Explore Other Toolkits

Composio

Composio search

Perplexityai

Browser tool

Frequently asked questions

What are the differences in Tool Router MCP and Google cloud vision MCP?+

Can I use Tool Router MCP with Pydantic AI?+

Can I manage the permissions and scopes for Google cloud vision while using Tool Router?+

How safe is my data with Composio Tool Router?+

Start with Google cloud vision.It takes 30 seconds.

Teams ship real agents on Composio