How to Use the Shotstack MCP in Google ADK

Q: How can Google ADK agents track render jobs with Shotstack?

Once a job starts via rendervideo, you get an ID. Pass that ID to getrenderstatus to check the progress. This lets your agent build reliable, multi-step cloud workflows.

Q: Does Shotstack handle large numbers of assets for Google ADK?

Yes. You use listassetsfromrender with a job ID to retrieve every associated asset. This makes it easy for your agent to audit the complete set of media used in any specific render.

Q: What's the best way to start video content generation with Shotstack and Google ADK?

You should first use listtemplates to find a suitable format. Then, your agent calls rendervideo, which handles the complexity of scaling up personalized videos based on BigQuery data triggers.

Q: Can I see my history of renders using Shotstack and Google ADK?

Running listrecentrenders gives you a clear log of past jobs. This helps your agent review performance trends or find the ID needed for a manual re-run.

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Connect Shotstack MCP to Google ADK

Create your Vinkius account to connect Shotstack to Google ADK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Shotstack with Google ADK

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Video Generation with MCP Server

You kick off the whole process by calling `render_video`, which returns a render ID. This allows your agent to generate highly personalized videos programmatically, scaling content creation from templates across massive datasets. You can monitor the job status using `get_render_status`. Your Google ADK workflow gets clear feedback on whether the video rendering finished or if it hit a snag.

Managing Media Sources for Google ADK

If your agent needs new media, use `ingest_media_source` to upload or fetch assets. This ensures that all content is properly sourced before the video rendering process begins. To audit what's available in the cloud, run `list_hosted_assets`. It shows every file you’ve stored, keeping your enterprise asset management clean.

Creating and Using Templates with MCP Server

Define a reusable video structure using `create_video_template` to save an edit. This lets your agent maintain consistency across millions of potential videos without rebuilding the template every time. Check all available formats instantly by calling `list_templates`. You'll see every pre-approved video template ready for consumption.

Setup guide

Set up Shotstack MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Shotstack tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Shotstack_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Shotstack tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Shotstack MCP in Google ADK

Once a job starts via `render_video`, you get an ID. Pass that ID to `get_render_status` to check the progress. This lets your agent build reliable, multi-step cloud workflows.

Yes. You use `list_assets_from_render` with a job ID to retrieve every associated asset. This makes it easy for your agent to audit the complete set of media used in any specific render.

You should first use `list_templates` to find a suitable format. Then, your agent calls `render_video`, which handles the complexity of scaling up personalized videos based on BigQuery data triggers.

Running `list_recent_renders` gives you a clear log of past jobs. This helps your agent review performance trends or find the ID needed for a manual re-run.

The server deals with ingested media sources and render job IDs. Your agent is handling source assets, which are temporary input files used during the video generation process within your Google Cloud environment.

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