How to Use the Creatomate MCP in Pydantic AI

Q: How do I configure Creatomate with Pydantic AI?

Install pydantic-ai-slimmcp. Create an MCPToolset pointing to your Vinkius MCP Server HTTP endpoint and add it to your Agent constructor. Do not use the deprecated MCPServerHTTP class.

Q: Can Pydantic AI list my Creatomate video automations?

Yes. The listvideoautomations tool pulls your configured workflows. The framework validates the returned workflow IDs so your agent can trigger them safely.

Q: Why did my Pydantic AI agent crash while reading Creatomate templates?

A validation error occurred. If listvideotemplates returns a data structure that violates your expected Pydantic model, the framework stops execution immediately to prevent hallucinations.

Type-safe Creatomate video generation for Pydantic AI agents.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Creatomate MCP to Pydantic AI

Create your Vinkius account to connect Creatomate to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Creatomate with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Validate template inputs strictly

Running `get_template_details` returns the required dynamic fields for any video file. Pydantic AI validates this schema at runtime against your predefined data models. If the API expects a string but gets an array, the agent fails loudly. You never waste API credits on malformed render requests because the types are guaranteed before execution.

Trigger renders through the MCP Server

The `render_video` tool accepts structured modifications and starts the encoding process. You pass exact layer names and the new text or image URLs to replace them. Model-agnostic design means you swap from Claude to a local Llama model without changing the tool logic. The framework ensures the payload always matches the required structure.

Monitor job completion reliably

Calling `get_render_status` grabs the current state of a specific encoding task. The agent reads the response to determine if the video is still processing or ready for download. You pair this with `list_recent_renders` to audit multiple jobs at once. Every status update parses into a strict Pydantic model directly from the MCP Server, eliminating silent corruption from unexpected JSON changes.

Setup guide

Set up Creatomate MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "creatomate-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Creatomate tools.",
)

result = await agent.run("List recent Creatomate transactions")
print(result.output)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Creatomate. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Creatomate now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Creatomate MCP in Pydantic AI

Install `pydantic-ai-slim[mcp]`. Create an `MCPToolset` pointing to your Vinkius MCP Server HTTP endpoint and add it to your Agent constructor. Do not use the deprecated `MCPServerHTTP` class.

Yes. The `list_video_automations` tool pulls your configured workflows. The framework validates the returned workflow IDs so your agent can trigger them safely.

A validation error occurred. If `list_video_templates` returns a data structure that violates your expected Pydantic model, the framework stops execution immediately to prevent hallucinations.

The framework supports Streamable HTTP and SSE transports. Your agent queries the status endpoints over these protocols to get real-time updates on the video encoding progress.

Vinkius routes your requests through an isolated sandbox environment. The text replacements, image URLs, and project IDs you send to the API are never logged anywhere.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript