Can my AI agent batch delete unused Uploadcare files?

Yes! Provide your agent with the list of unused UUIDs or ask it to identify temporary incomplete uploads, and simply command it to `batch delete these assets`. The agent uses the `batch_delete_files` tool to permanently erase them from the CDN instantly, freeing up your project's storage.

How can I quickly check my current CDN bandwidth and storage usage?

Instead of digging through the web dashboard, ask your AI agent to `get project info`. It instantly fetches your Uploadcare project-level metadata, returning your precise storage usage (bytes), traffic bandwidth usage, and active file count. Perfect for quick billing audits.

Will my temporary UI uploads expire automatically?

By default, temporary files uploaded via your front-end will be wiped after 24 hours. To prevent this, you can ask your agent to `store this file ` or `batch store` a bunch of UUIDs. The agent communicates with Uploadcare to mark the files as permanently stored, saving them from the garbage collector.

Uploadcare MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Uploadcare
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Uploadcare through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Uploadcare "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Uploadcare?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Uploadcare MCP Server

Connect your Uploadcare account to any AI agent to fully manage your file handling and CDN media infrastructure via natural conversation.

Pydantic AI validates every Uploadcare tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

File Management — List uploaded assets, retrieve specific file technical metadata (like dimensions and CDN URLs), and manage permanent storage states.
Bulk Operations — Efficiently batch store or batch delete multiple temporary or permanent files in a single operation.
File Transport — Copy existing files manually to local or remote storage targets, directly through your AI agent.
Groups & Collections — List immutable file collections (groups) and inspect which individual files are contained within them.
Project Analytics — Retrieve your Uploadcare project-level metadata, checking your current account storage and bandwidth consumption in real time.

The Uploadcare MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Uploadcare to Pydantic AI via MCP

Follow these steps to integrate the Uploadcare MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Uploadcare with type-safe schemas

Why Use Pydantic AI with the Uploadcare MCP Server

Pydantic AI provides unique advantages when paired with Uploadcare through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Uploadcare integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Uploadcare connection logic from agent behavior for testable, maintainable code

Uploadcare + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Uploadcare MCP Server delivers measurable value.

Type-safe data pipelines: query Uploadcare with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Uploadcare tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Uploadcare and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Uploadcare responses and write comprehensive agent tests

Uploadcare MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Uploadcare to Pydantic AI via MCP:

batch_delete_files

This action is irreversible. Permanently removes multiple files in a single operation

batch_store_files

Marks multiple temporary files as permanently stored

copy_file

g. S3). Copies an existing file to local or remote storage

delete_file

This action is irreversible. Permanently removes a file and its variants from Uploadcare

get_file_details

Retrieves technical metadata for a specific Uploadcare file

get_group_details

Retrieves information about a specific file group

get_project_info

Retrieves project-level metadata and usage statistics

list_file_groups

Lists immutable file collections (groups) in the project

list_files

Supports pagination via limit. Lists files stored in your Uploadcare project

store_file

Marks a temporary file as permanently stored

Example Prompts for Uploadcare in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Uploadcare immediately.

"What is our current project storage and bandwidth usage?"

"Can you check the dimensions and CDN URL for file UUID `9cd83...`?"

"Batch delete these 4 outdated temporary images: `e33b...`, `f55a...`, `8c11...`, `ab99...`."

Troubleshooting Uploadcare MCP Server with Pydantic AI

Common issues when connecting Uploadcare to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Uploadcare + Pydantic AI FAQ

Common questions about integrating Uploadcare MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Uploadcare MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.