How to Use the UUID Generator Engine MCP in Google ADK

Q: Can I use the UUID Generator Engine in the Google ADK for repeatable IDs?

Yes, you can run v5 via generateuuid. By setting a fixed namespace and name, you ensure that the agent always returns the exact same identifier, which is great for consistent testing.

Q: What if I need random IDs using the UUID Generator Engine with Google ADK?

Just call generateuuid and select v4. This function produces a standard random UUID that works whenever you don't need specific time or name correlation.

Build enterprise agents that use the UUID Generator Engine for data integrity on Google ADK.

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Connect UUID Generator Engine MCP to Google ADK

Create your Vinkius account to connect UUID Generator Engine 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 UUID Generator Engine with Google ADK

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Create sortable IDs ideal for BigQuery keys.

For primary keys in your cloud infrastructure, call `generate_uuid` and set v7. This time-ordered UUID type adheres to RFC 9562 standards. Your agent can now ensure that any record created via the Google ADK will have an ID that naturally sorts by when it was generated.

Maintain consistent data linking across Vertex AI.

If you need to link records across different services, use v5 with `generate_uuid`. By providing a fixed namespace and name, the agent guarantees that the ID will always be the same. This repeatability is essential when building complex pipelines on Google Cloud.

Generate quick random IDs for temporary records.

When speed matters more than traceability, `generate_uuid` and v4 handles it. This outputs a standard random UUID. It's the simplest way to assign an ID when you just need something unique right now.

Setup guide

Set up UUID Generator Engine 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 UUID Generator Engine 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="UUID Generator Engine_agent",
    model="gemini-2.0-flash",
    instruction="You have access to UUID Generator Engine tools via MCP.",
    tools=mcp_tools,
)

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Common questions about UUID Generator Engine MCP in Google ADK

The engine generates v7, time-ordered UUIDs following RFC 9562. This allows your agents to assign primary keys that sort chronologically right out of the box.

Yes, you can run v5 via `generate_uuid`. By setting a fixed namespace and name, you ensure that the agent always returns the exact same identifier, which is great for consistent testing.

Just call `generate_uuid` and select v4. This function produces a standard random UUID that works whenever you don't need specific time or name correlation.

It is built to handle enterprise-grade IDs conforming to RFC 9562. The predictable nature of v7 and v5 makes it ideal for BigQuery integration.

It handles generating standard UUID strings (v4, v5, v7). The agent passes contextual inputs and receives these structured string outputs for use in your cloud workflows.

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