Give Your AI Agents a Sense of Time

Your AI assistant just scheduled a meeting for "tomorrow at 2 PM" – but which timezone? Your agent-powered deployment script needs to log timestamps consistently across global infrastructure. Your chatbot keeps giving users stale information because it has no concept of "now."

These aren't edge cases. They're daily friction points when building with AI agents that need temporal awareness.

The Time Problem with AI Systems

Most AI agents live in a timeless bubble. They can discuss dates and times, but they can't actually know what time it is right now or handle timezone conversions reliably. When you're building agents that need to:

• Schedule events and reminders
• Log activities with proper timestamps
• Provide time-sensitive information
• Coordinate across timezones
• Generate reports with current data

You end up writing the same datetime utilities over and over, or worse – dealing with inconsistent time handling across your agent ecosystem.

Dead Simple Time Access for MCP

MCP-timeserver gives your agents reliable datetime capabilities through the Model Context Protocol. No complex setup, no external dependencies – just clean time access that works consistently.

Get current time anywhere:

get_current_time()  # "The current time is 2024-12-18 19:59:36"

Access timezone-specific times via URI:

datetime://Europe/London/now
datetime://America/New_York/now  
datetime://Asia/Tokyo/now

Convert between timezones:

{
  "datetime": "2025-01-07T13:35:12Z",
  "to_tz": "America/Los_Angeles"
}

Where This Actually Matters

Multi-timezone team coordination: Your Slack bot can accurately tell remote team members "the daily standup starts in 30 minutes" regardless of where they're located.

Automated reporting: Your analytics agent generates reports with proper timestamps instead of confusing users with server time that means nothing to them.

Event scheduling: Your calendar assistant understands "schedule this for 3 PM Pacific" and converts it properly for attendees in different zones.

Log aggregation: Your monitoring agents timestamp incidents consistently, making debugging across distributed systems actually possible.

Content scheduling: Your social media agent posts content at optimal local times for different regions without manual timezone calculations.

Integration in 30 Seconds

Add to your MCP server configuration:

{
  "mcpServers": {
    "MCP-timeserver": {
      "command": "uvx",
      "args": ["MCP-timeserver"]
    }
  }
}

That's it. Your agents immediately gain time awareness without you writing a single datetime utility function.

Why This Beats DIY Solutions

You could build your own datetime handling, but MCP-timeserver eliminates the usual headaches:

• No timezone database management – stays current automatically
• Consistent formatting – ISO-8601 by default, no format juggling
• MCP-native – integrates seamlessly with your existing agent architecture
• Zero dependencies – runs anywhere Python runs
• Stateless – no database, no complex setup

When your agents need to know what time it is, they just ask. When they need timezone conversions, they just request them. The complexity stays hidden while your agents get smarter about time.

Your AI systems should understand time as naturally as they understand text. MCP-timeserver makes that happen without the usual datetime development pain.