How to Use the Creatomate MCP in LlamaIndex

Q: Does LlamaIndex support filtering MCP tools?

You can pass an allowedtools list when initializing the spec. This restricts the agent to specific actions like checking status.

Turn your video templates into a searchable LlamaIndex knowledge base to ground your agent in real media data.

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Connect Creatomate MCP to LlamaIndex

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

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Setup Creatomate with LlamaIndex

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Index Video Assets with this MCP Server

RAG usually stops at text documents. Now you can point your indexer at a live media production environment. Your agent pulls everything via `list_video_templates` and `list_video_automations`. This creates a semantic map of your available video workflows.

Grounded Video Generation

Hallucinations ruin automated video projects. An agent guessing a template ID will crash the render queue. By querying the index first, the agent passes exact, verified dynamic fields into `render_video`. It knows the structure because it read `get_template_details` beforehand.

Retrieval-Augmented Media Management

Finding the right B-roll takes time. You can ask your application about past sessions and get answers based on actual API responses. The agent searches through `list_media_assets` and `list_recent_renders`. It finds out exactly what footage was used in last week's campaign.

Setup guide

Set up Creatomate MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Creatomate MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Creatomate tools.",
)
response = await agent.run("List recent Creatomate data")

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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.

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Common questions about Creatomate MCP in LlamaIndex

Install llama-index-tools-mcp. Use BasicMCPClient with your Vinkius URL, then convert the specs into a tool list.

Yes. The agent indexes the output of the template tools, allowing you to run semantic queries against your video layouts.

You can pass an allowed_tools list when initializing the spec. This restricts the agent to specific actions like checking status.

The agent reads the error response from the tool call. It can then query the index to find the correct template structure and try again.

Vinkius operates on a strict zero-trust architecture. The connection authenticates via a single endpoint token, processing your media files in memory without ever writing them to disk.

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