How to Use the RenderMe MCP in Google ADK

Q: How does Google ADK interact with the RenderMe MCP Server?

You define an McpToolset using your RenderMe endpoint. Once passed to your LlmAgent, it exposes the full suite of video tools as native functions.

Q: Can I filter tools when using RenderMe with Google ADK?

Yes, you can use a toolnames filter to restrict which functions your agent can see. This limits the agent's surface area to only the tools you explicitly approve.

Integrate RenderMe video generation into your Google ADK enterprise infrastructure.

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Connect RenderMe MCP to Google ADK

Create your Vinkius account to connect RenderMe 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 RenderMe with Google ADK

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Execute RenderMe jobs via Google ADK

Connect your Gemini-powered agents to the RenderMe engine using the `McpToolset`. Triggering a `create_video_render_job` becomes a standard part of your agent's decision-making process. Your agent can query the system using `list_video_projects` to determine the current state of your pipeline. This keeps your video production tightly coupled with your existing cloud data.

Retrieve template data with Google ADK

Your agent can fetch specific template configurations using `get_template_details`. It ensures that every parameter passed to a render job is accurate and up to date. This workflow allows for dynamic content generation. By combining `list_video_templates` with your BigQuery data, your agent creates personalized videos at scale.

Monitor render status in Google ADK

Maintain visibility over your render pipeline by calling `get_render_job_status` from your agent. It allows you to poll for completion or handle failures programmatically. This is critical for enterprise agents that manage long-running tasks. You can also use `list_configured_webhooks` to verify that your notification triggers are active and ready.

Setup guide

Set up RenderMe 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 RenderMe 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="RenderMe_agent",
    model="gemini-2.0-flash",
    instruction="You have access to RenderMe tools via MCP.",
    tools=mcp_tools,
)

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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 RenderMe. 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 RenderMe MCP in Google ADK

You define an `McpToolset` using your RenderMe endpoint. Once passed to your `LlmAgent`, it exposes the full suite of video tools as native functions.

Yes, you can use a tool_names filter to restrict which functions your agent can see. This limits the agent's surface area to only the tools you explicitly approve.

The server supports both Stdio and HTTP transports. You can choose the connection method that best fits your Google Cloud deployment architecture.

Absolutely. Since your agent can hold 1M+ tokens, it can easily process long lists of `list_uploaded_assets` without losing track of your media library.

All communications are isolated within the Vinkius V8 sandbox. The server only processes your account's render job IDs, project names, and template configurations.

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