Simple Timeserver

Access accurate local and UTC time information.

Installation Instructions

README: https://github.com/andybrandt/mcp-simple-timeserver

MCP Simple Timeserver

One of the strange design decisions Anthropic made was depriving Claude of timestamps for messages sent by the user or current time in general. Poor Claude can't tell what time it is! mcp-simple-timeserver is a simple MCP server that fixes that.

This server provides two tools:

• get_local_time provides the current local time and timezone information from the user's machine. This way Claude can know what time it is at the user's location. He can also calculate how much time passed since his last interaction with the user should he want to do so.
• get_utc provides current UTC time obtained from an NTP time server.

Installation

Installing via Smithery

To install Simple Timeserver for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install mcp-simple-timeserver --client claude

Manual Installation

First install the module using:

pip install mcp-simple-timeserver

Then configure in MCP client - the Claude desktop app.

Under Mac OS this will look like this:

"mcpServers": {
  "simple-timeserver": {
    "command": "python",
    "args": ["-m", "mcp_simple_timeserver"]
  }
}

Under Windows you have to check the path to your Python executable using where python in the cmd (Windows command line).

Typical configuration would look like this:

"mcpServers": {
  "simple-timeserver": {
    "command": "C:\\Users\\YOUR_USERNAME\\AppData\\Local\\Programs\\Python\\Python311\\python.exe",
    "args": ["-m", "mcp_simple_timeserver"]
  }
}

Web Server Variant

This project also includes a network-hostable version that can be deployed as a standalone web server. For instructions on how to run and deploy it, please see the Web Server Deployment Guide.

Or you can simply use my server by adding it under https://mcp.andybrandt.net/timeserver to Claude. (It does not work with ChatGPT since it currently works only with MCP servers that implement search() and fetch() tools to serve data in response to LLM's querries).