How to Use the Time MS Converter MCP in Google ADK

Q: How do I integrate the Time MS Converter with a Google ADK agent?

You'll instantiate an McpToolset with the server URL provided by Vinkius. Then, just pass that toolset into the LlmAgent constructor. The agent will then have access to the time conversion tool.

Connect your Google ADK agent to a deterministic time parser. Stop guessing at milliseconds in your Google Cloud workflows.

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Connect Time MS Converter MCP to Google ADK

Create your Vinkius account to connect Time MS Converter 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 Time MS Converter with Google ADK

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Perplexity Vinkius runs on Gemini

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Deterministic Time for Gemini

Your Gemini-powered agent can reason over a million tokens, but it shouldn't be doing basic math. When you need to set a TTL on a resource or schedule a Vertex AI job, you need an exact number, not a "best guess" from a language model. This MCP server provides one simple tool: `convert_time`. Your agent passes it a string like "7d" and gets back a precise millisecond integer. It makes time-based operations on Google Cloud reliable. You can also pass it milliseconds to get a human-readable string.

A Purpose-Built MCP Server for GCP

You're building on Google Cloud, so every part of your stack needs to be enterprise-grade. This tool acts as a specialized, reliable function for your ADK agent, just like calling a dedicated Cloud Function. Imagine your agent needs to set a retention policy on a BigQuery table. Instead of fumbling with prompts, it calls this MCP tool, gets the exact duration in milliseconds, and constructs a flawless API call. It's about bringing infrastructure-level reliability to your agent's toolset.

Offload Math, Focus on Reasoning

Don't burn your agent's powerful long-context window on trying to figure out how many milliseconds are in three weeks. It's an inefficient use of the model and introduces a point of failure. Let the agent focus on the "what" and "why" of a task. When it comes to the "how long," it just calls this tool. This separation of concerns makes your agent's logic cleaner and its actions more dependable.

Setup guide

Set up Time MS Converter 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 Time MS Converter 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="Time MS Converter_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Time MS Converter tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Time MS Converter MCP in Google ADK

You'll instantiate an `McpToolset` with the server URL provided by Vinkius. Then, just pass that toolset into the `LlmAgent` constructor. The agent will then have access to the time conversion tool.

It might get it right most of the time, but "most of the time" isn't good enough for production infrastructure. This tool removes the probability, giving you a correct answer every time without fail.

Absolutely. It's perfect for calculating timeouts or scheduling delays for any Google Cloud service. Your agent can determine the business logic ("run this in 3 days") and use the tool to get the exact technical parameter.

The tool will return an error, which your agent can handle. It's designed to fail predictably instead of returning a wrong number, so you can build robust error handling into your agent's logic.

Your data never touches our disks. The server receives a time string, like "90s", converts it in memory within a zero-trust sandbox, and sends back the result. The entire operation is stateless and ephemeral.

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