How do I get a Creatomate API Key?

Log in to your Creatomate account, select your project, and navigate to **Project Settings > API Keys** to generate a secret key.

Can I provide dynamic text for videos?

Yes, you can use the 'modifications' parameter in the render_video tool to swap text, images, or colors defined in your template.

What is the rendering time?

Rendering time depends on video length and complexity, but Creatomate is optimized for speed. You can use the get_render_status tool to check when it's done.

Creatomate MCP Server for Pydantic AI 9 tools — connect in under 2 minutes

Name: Creatomate
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 9 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Creatomate 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 Creatomate "
            "(9 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Creatomate?"
    )
    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 Creatomate MCP Server

Integrate Creatomate, the powerful video automation platform, directly into your AI workflow. Generate high-quality videos from templates, manage your media assets, and monitor rendering tasks using natural language.

Pydantic AI validates every Creatomate tool response against typed schemas, catching data inconsistencies at build time. Connect 9 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

Automated Rendering — Trigger new video renders using dynamic templates and custom modifications via chat.
Template Exploration — List and inspect available video templates and their dynamic fields.
Asset Management — Manage your library of images, videos, and audio files used in your projects.
Status Tracking — Monitor the progress of rendering tasks and retrieve final video URLs in real-time.

The Creatomate MCP Server exposes 9 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 Creatomate to Pydantic AI via MCP

Follow these steps to integrate the Creatomate 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 9 tools from Creatomate with type-safe schemas

Why Use Pydantic AI with the Creatomate MCP Server

Pydantic AI provides unique advantages when paired with Creatomate 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 Creatomate integration code

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

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

Creatomate + Pydantic AI Use Cases

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

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

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

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

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

Creatomate MCP Tools for Pydantic AI (9)

These 9 tools become available when you connect Creatomate to Pydantic AI via MCP:

get_project_settings

Retrieve settings and metadata for the current project

get_render_status

Check the status and get the URL of a rendered video

get_template_details

Get structure and dynamic fields for a template

list_media_assets

List uploaded media assets (images, videos, audio)

list_recent_renders

List recent video rendering tasks and their status

list_video_automations

List automated video workflows

list_video_templates

List all video templates available in your project

render_video

Trigger a new video render using a template and modifications

search_templates_by_name

Search for video templates by name

Example Prompts for Creatomate in Pydantic AI

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

"Render a video using template 't8s9df7' with the text 'Flash Sale!' and background image 'sale.jpg'."

"What's the status of my video render 'r123abc'?"

"List all video templates in my project."

Troubleshooting Creatomate MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Creatomate + Pydantic AI FAQ

Common questions about integrating Creatomate 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 Creatomate MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.