Creatomate MCP Server for LlamaIndex 9 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Creatomate as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Creatomate. "
"You have 9 tools available."
),
)
response = await agent.run(
"What tools are available in Creatomate?"
)
print(response)
asyncio.run(main())
* 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.
LlamaIndex agents combine Creatomate tool responses with indexed documents for comprehensive, grounded answers. Connect 9 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the Creatomate MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
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
Why Use LlamaIndex with the Creatomate MCP Server
LlamaIndex provides unique advantages when paired with Creatomate through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Creatomate tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Creatomate tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Creatomate, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Creatomate tools were called, what data was returned, and how it influenced the final answer
Creatomate + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Creatomate MCP Server delivers measurable value.
Hybrid search: combine Creatomate real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Creatomate to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Creatomate for fresh data
Analytical workflows: chain Creatomate queries with LlamaIndex's data connectors to build multi-source analytical reports
Creatomate MCP Tools for LlamaIndex (9)
These 9 tools become available when you connect Creatomate to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting Creatomate to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpCreatomate + LlamaIndex FAQ
Common questions about integrating Creatomate MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Creatomate with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Creatomate to LlamaIndex
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.