screentime-mcp-server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_screentimeB | Get app usage data for a specific date. Returns per-app usage grouped by hour with human-readable app names. |
| screentime_sqlA | Run a custom SQL query against macOS knowledgeC.db (Screen Time database). Use ZOBJECT table with ZSTREAMNAME='/app/usage'. Timestamps use Core Data epoch (978307200 offset from Unix). Returns raw pipe-separated results. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
get_screentime and screentime_sql have distinct roles: one is a convenience wrapper for date-specific usage, the other allows arbitrary SQL. However, an agent might be unsure when to use the specific date tool versus writing SQL, especially since both can return usage data.
The names follow different conventions: get_screentime uses a clear verb_noun pattern, while screentime_sql is noun-based and lacks a verb, making the set feel inconsistent. This mixing reduces predictability.
Two tools is quite thin for a server that could expose more granular Screen Time operations (e.g., date ranges, app lists, totals). The SQL escape hatch adds power, but the surface still feels minimal.
The combination of a targeted get_screentime tool and a general SQL query tool covers most retrieval needs, including custom queries. Minor gaps exist (e.g., no built-in date-range summary or app enumeration), but the SQL tool allows agents to compensate.