Temporal Context MCP

Example Use Cases

• 1

  Adapt responses based on user daily schedules.

• 2

  That require context-aware recommendations tied to specific time periods.

• 3

  Prioritize interactions according to user-defined temporal priorities.

Description

This MCP server enables AI agents to dynamically adjust their behavior by evaluating user-defined temporal contexts specified via cron expressions. It resolves active contexts based on current time and priority, then derives tailored recommendations to guide AI responses. The system is easy to configure with JSON files and exposes a simple API for retrieving current context and recommendations, enhancing AI adaptability and relevance.