Temporal Context
byfedeegmz
0Empowers AI assistants to adapt their responses and behavior intelligently based on the user's schedule and routines.
About
This Model Context Protocol (MCP) server provides dynamic temporal context to AI agents, allowing them to intelligently adapt. Users define `TemporalContext` objects, each with a cron-based `TimePattern`, in a simple JSON file. The server continuously matches the current time to these patterns, activating the relevant context. This active context then derives a `Recommendation` object, guiding the AI agent on aspects like response style, formality, suggested tools, and topics to avoid, ensuring the AI's interactions are always relevant and appropriate for the user's current activity or time of day.
Key Features
- Priority-based resolution for overlapping active contexts
- API endpoint to retrieve active temporal context and recommendations
- Simple JSON-based persistence for configuration
- 0 GitHub stars
- User-definable temporal contexts with cron expressions
- Dynamic derivation of AI recommendations (response style, formality, tools)
Use Cases
- Guiding AI agents to avoid certain topics during sensitive or focused periods.
- Tailoring AI agent communication style based on working hours vs. leisure time.
- Enabling AI assistants to suggest specific tools relevant to the user's current activity.
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