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How to integrate Uploadcare MCP with Pydantic AI

Connect Pydantic AI to Uploadcare MCP. List all uploaded files from last week, rotate image file by 90 degrees clockwise, and more using natural language, with authentication handled for you.

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Uploadcare is a file handling platform for uploading, storing, and delivering files at scale. It streamlines file management, processing, and delivery for web and mobile apps.

34 Tools

Introduction

This guide walks you through connecting Uploadcare to Pydantic AI using the Composio tool router. By the end, you'll have a working Uploadcare agent that can upload files from URLs, store and delete files, manage file groups and metadata, run virus scans, and set up webhooks through natural language commands.

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

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

Also integrate Uploadcare with

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAIAutoGen

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 Uploadcare
  • 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 Uploadcare 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 Uploadcare MCP server, and what's possible with it?

The Uploadcare MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Uploadcare account. It provides structured and secure access to your file storage, processing, and delivery pipeline, so your agent can perform actions like listing files, retrieving file info, managing webhooks, rotating images, and handling file metadata on your behalf.

  • Comprehensive file listing and retrieval: Ask your agent to list all files stored in your Uploadcare project, filter by criteria, or fetch detailed metadata for any file.
  • Direct file download and sharing: Effortlessly generate secure, temporary download links for your files so you can share them or integrate with other services.
  • Automated image processing: Let your agent rotate images by 90, 180, or 270 degrees, making quick edits or transformations without manual intervention.
  • Webhook management for event automation: Easily create, list, or delete webhooks so your agent can subscribe to file events and enable real-time notifications or integrations.
  • Metadata and group management: Enable your agent to update or delete file metadata and organize files into groups for streamlined file handling and workflows.

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:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
2

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.
3

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 Uploadcare
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

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
5

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 Uploadcare
  • MCPServerStreamableHTTP connects to the Uploadcare MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

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 Uploadcare
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["uploadcare"],
    )
    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 Uploadcare 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
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
uploadcare_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[uploadcare_mcp],
    instructions=(
        "You are a Uploadcare assistant. Use Uploadcare tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Uploadcare endpoint
  • The agent uses GPT-5 to interpret user commands and perform Uploadcare operations
  • The instructions field defines the agent's role and behavior
8

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 Uploadcare.\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
  • Uploadcare API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

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 Uploadcare 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 Uploadcare
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["uploadcare"],
    )
    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
    uploadcare_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[uploadcare_mcp],
        instructions=(
            "You are a Uploadcare assistant. Use Uploadcare 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 Uploadcare.\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 Uploadcare through Composio's Tool Router. With this setup, your agent can perform real Uploadcare 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 + Uploadcare 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 Uploadcare action and event your agent gets out of the box.

Check AWS Rekognition Moderation Status

Tool to check the execution status of AWS Rekognition Moderation labels detection.

Check Remove.bg Status

Tool to check Remove.

Copy Uploadcare File to Local Storage

Tool to copy a file to local storage within the same Uploadcare project.

Create File Group (Upload API)

Tool to create a file group from already uploaded files using Uploadcare's Upload API.

Create Uploadcare webhook

Create a new webhook subscription to receive notifications when file events occur.

Delete File Metadata Key

Tool to delete a specific metadata key from an Uploadcare file.

Batch Delete Uploadcare Files

Delete up to 100 files from Uploadcare storage in a single request.

Delete Uploadcare Group

Tool to delete a file group.

Delete Uploadcare File

Tool to delete a single file from Uploadcare storage by UUID.

Delete Uploadcare Webhook

Permanently deletes a webhook subscription from your Uploadcare project.

Delete Uploadcare Webhook by URL

Tool to delete a webhook subscription by its target URL.

Execute ClamAV virus scan

Start an asynchronous ClamAV virus scan on an uploaded file, optionally purging infected files, and receive a request ID to track its status.

Get AWS Rekognition Execution Status

Tool to check AWS Rekognition execution status for label detection.

Get ClamAV Scan Status

Tool to check the execution status of a ClamAV virus scan.

Get File Group Info (Upload API)

Tool to get information about a file group from the Upload API.

Get Uploadcare File Info

Tool to get information about a specific file.

Get File Metadata

Tool to retrieve all metadata key-value pairs associated with an Uploadcare file.

Get File Metadata Key Value

Tool to get the value of a specific metadata key for an Uploadcare file.

Get Uploadcare Group Info

Tool to get information about a specific file group.

Get Uploadcare Project Info

Tool to get information about the current Uploadcare project.

Get Uploaded File Info

Tool to get information about an uploaded file using Uploadcare's Upload API.

Get URL Upload Status

Tool to check the status of a URL upload task.

Mirror Uploadcare Image

Tool to mirror an image horizontally via Uploadcare CDN.

List Uploadcare Files

List files in an Uploadcare project with pagination and optional filtering.

List Uploadcare Groups

Tool to list groups in the project.

List Uploadcare Webhooks

Retrieves all webhook subscriptions for the authenticated Uploadcare project.

Rotate Image

Generate and verify a CDN URL for an uploaded image rotated counterclockwise by 90, 180, or 270 degrees.

Start Multipart Upload

Tool to start a multipart upload session for files larger than 100MB.

Batch Store Files

Tool to store multiple files in one request.

Store Uploadcare File

Tool to mark an Uploadcare file as permanently stored.

Store Single Uploadcare File

Tool to store a single file by UUID permanently.

Update File Metadata Key

Tool to update or set the value of a specific metadata key for a file.

Update Uploadcare webhook

Update an existing webhook subscription by its ID.

Upload File from URL

Tool to upload a file from a publicly available URL to Uploadcare.

FRAMEWORKS

How to build Uploadcare MCP Agent with another framework

Claude Code logo

Claude Code

Use Uploadcare MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Uploadcare MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Uploadcare MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Uploadcare MCP with Claude Agent SDK

Codex logo

Codex

Use Uploadcare MCP with Codex

OpenClaw logo

OpenClaw

Use Uploadcare MCP with OpenClaw

Hermes logo

Hermes

Use Uploadcare MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Uploadcare MCP with Atomic Agent

Google ADK logo

Google ADK

Use Uploadcare MCP with Google ADK

LangChain logo

LangChain

Use Uploadcare MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Uploadcare MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Uploadcare MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Uploadcare MCP with LlamaIndex

CrewAI logo

CrewAI

Use Uploadcare MCP with CrewAI

AutoGen logo

AutoGen

Use Uploadcare MCP with AutoGen

FAQ

Frequently asked questions

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

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

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