How to Use the Time MS Converter MCP in OpenAI Agents SDK

Q: What time formats does the Time MS Converter support with my OpenAI Agents SDK?

It handles standard abbreviations like d for days, h for hours, m for minutes, and s for seconds. It also parses combinations and decimals, like "1.5h" or "2d 6h".

Stop your OpenAI Agent from failing at math. Get exact milliseconds for scheduling and timeouts, every single time.

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Connect Time MS Converter MCP to OpenAI Agents SDK

Create your Vinkius account to connect Time MS Converter to OpenAI Agents SDK — 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 OpenAI Agents SDK

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Stop Agent Math Hallucinations

Your agent is great at language, not arithmetic. Asking it to convert "1.5 days" to milliseconds in a prompt is asking for trouble, especially when a wrong number can break a production workflow. This MCP server fixes that. The `convert_time` tool takes a human string like "3h 30m" and returns the exact integer in milliseconds. Your OpenAI Agent auto-discovers and calls it, getting a reliable number back for API timeouts or scheduling tasks. It even works in reverse.

Built for Production Agentic Workflows

The OpenAI Agents SDK is designed for building real products, not just demos. That means every component needs to be predictable. Integrating a non-deterministic math function via prompting is a major liability. By using this MCP tool, the conversion becomes a discrete, traceable step. OpenAI's native tracing will show the exact input and output from the server. It's a simple way to add a critical guardrail to your agent's logic.

Simplify Your OpenAI Agent's Logic

Stop wasting tokens and complexity on prompt engineering for basic math. Trying to force an LLM to reliably calculate time is a losing battle against edge cases. Just tell your agent to use the available tool when it needs a duration in milliseconds. The prompt becomes simpler, the agent's reasoning is more focused, and the whole system is more reliable. It's one less thing you have to worry about.

Setup guide

Set up Time MS Converter MCP in OpenAI Agents SDK

Prerequisites

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

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Time MS Converter tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Time MS Converter tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Time MS Converter tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Time MS Converter Agent",
            instructions="You have access to Time MS Converter tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Time MS Converter MCP in OpenAI Agents SDK

It's automatic. Once you pass the MCP Server endpoint to your Agent constructor, the SDK auto-discovers the tool. Your agent can then decide to call it without any extra code from you. This is a core benefit of the MCP standard.

Because language models are probabilistic and can't guarantee mathematical accuracy. For critical tasks like scheduling, a 1% failure rate is too high. This tool is deterministic, so it's right 100% of the time.

Yes, that's the primary use case. Your agent gets a reliable millisecond value from the tool, which you can then pass to a scheduler like Celery, BullMQ, or a cloud provider's task queue.

It handles standard abbreviations like `d` for days, `h` for hours, `m` for minutes, and `s` for seconds. It also parses combinations and decimals, like "1.5h" or "2d 6h".

The server only ever sees the time strings you send it, like "10m". It processes that string in an ephemeral, sandboxed environment and immediately returns the millisecond value. No data is ever stored, logged, or associated with your account.

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