jubnl
c1b9d11173
Adds the complete TREK documentation wiki covering installation, trip planning, admin panel, MCP/AI integration, addons, and operations. Also fixes encrypt-at-rest gaps: mapbox_access_token, Synology credentials, per-user webhook/ntfy tokens, and photo passphrases are now rotated by migrate-encryption.ts and stored encrypted via settingsService.
2.0 KiB
MCP Prompts
TREK includes built-in MCP prompts — pre-built context loaders that tell your AI client how to summarize or present your trip data in a structured way. Prompts are a standard MCP feature: compatible clients can invoke them by name to get a ready-made starting point for common tasks.
Built-in prompts
| Prompt | Addon required | Description |
|---|---|---|
trip-summary |
— | Loads a formatted summary of a trip: dates, member list, day count, number of places per day, packing progress, budget total, reservation count, and collab note count. Use this before asking the AI to plan or modify a trip. |
packing-list |
Packing | Returns the full packing checklist for a trip, grouped by category, with each item marked checked or unchecked. |
budget-overview |
Budget | Returns a budget summary for a trip — total spend, breakdown by category (sorted descending), and a per-person cost estimate. |
token_auth_notice |
— | Deprecation notice for sessions authenticated with a static trek_ token. Only available in static-token sessions. Explains that the token will stop working in a future version and how to migrate to OAuth 2.1. |
packing-list and budget-overview are only registered when the corresponding addon is enabled on your TREK instance.
token_auth_notice is only registered when the current session was authenticated with a legacy static API token — it does not appear in OAuth sessions.
How to use prompts
In a compatible MCP client (such as Claude.ai or Claude Desktop), prompts typically appear as slash commands or in a prompts panel. You select the prompt, supply any required arguments (such as a tripId), and the client sends the formatted context to the AI before your next message.
For example, invoking trip-summary with a trip ID gives the AI a compact snapshot of that trip — days, members, budget, packing — without needing to call multiple tools one by one.