How to Use the Meshy (3D AI) MCP in Google ADK

Connect your Google ADK agents to Meshy (3D AI) for high-speed geometry generation.

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Connect Meshy (3D AI) MCP to Google ADK

Create your Vinkius account to connect Meshy (3D AI) to Google ADK 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 Meshy (3D AI) with Google ADK

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Google ADK agents generating 3D content

Invoke `create_image_to_3d` to turn visual assets from your cloud storage into 3D models. Your Google ADK agent acts as the controller, managing the input and output flow. This allows you to automate the conversion of large image sets into usable 3D assets. You keep the logic within your existing Google Cloud environment.

Mesh optimization within Google ADK

Use `create_remesh` to clean up generated assets so they perform well in your rendering engine. Your Google ADK agent can sequence these steps to ensure clean topology. This minimizes the need for manual cleanup. You get usable models that fit your strict performance budgets without extra human intervention.

Printability verification for Google ADK

Check if your generated models are ready for production using `analyze_printability`. Your Google ADK agent evaluates the mesh structure and flags potential issues before you spend time on physical fabrication. If the tool identifies flaws, call `repair_printability` to fix them. Your agent handles the iteration loop until the mesh is production-ready.

Setup guide

Set up Meshy (3D AI) 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 Meshy (3D AI) 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="Meshy (3D AI)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Meshy (3D AI) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Meshy (3D AI) MCP in Google ADK

You configure the McpToolset with your server URL. The tools then appear as native functions within your agent's capability list.

Absolutely. The server supports the scale required for enterprise tasks, and you can restrict tools using the tool_names filter.

Yes. Your agent can hold the state of multiple generation tasks in memory, allowing for complex multi-step workflows.

The server exposes all 17 tools. You can limit your agent's access by passing a specific list to the toolset configuration.

Your data is processed through the Meshy API endpoint. Security is managed via your unique API token, ensuring only your agent can access your generated meshes.

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