How to Use the Time MS Converter MCP in LangChain

Stop letting LLMs guess timeouts. Force exact math in your LangChain pipelines with deterministic conversions.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Time MS Converter MCP to LangChain

Create your Vinkius account to connect Time MS Converter to LangChain — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

GDPR Included with Plan

Setup Time MS Converter with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity Vinkius runs on Gemini

Gemini

Grok

Hardcoded math for LangChain pipelines

The `convert_time` tool stops your agent from doing mental math. You pass a string like "1.5h" and get exact milliseconds back. Probabilistic models fail at basic arithmetic. If your ReAct agent guesses a timeout value, your pipeline hangs or crashes. This server acts as a strict calculator link in your chain.

Reverse formatting for raw integers

Sometimes you get raw integers from a database query and need to know what they mean. Pass a millisecond number as a string, and it returns the human-readable format. It handles days, hours, minutes, and seconds. No complex cron expressions, just straight duration translations.

Built for multi-step reasoning

LangSmith tracing will show you exactly what went into the conversion and what came out. You get full observability on the latency and token usage. Your agent decides when to call this MCP server before passing the result to a database or scheduling API. It runs instantly.

Setup guide

Set up Time MS Converter MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Time MS Converter tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "time-ms-converter-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Time MS Converter transactions"
    })
    print(result["messages"][-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Vercel MS. 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.