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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
CLIPPY_PYTHONNoPath to a specific Python interpreter for Clippy to use. The packaged app runs CLIPPY_PYTHON if set, otherwise `python3` (Linux/macOS) or `python` (Windows) from PATH. Advanced: point Clippy at a specific interpreter before launch, e.g. `$env:CLIPPY_PYTHON = "C:\path\to\python.exe"` or `export CLIPPY_PYTHON=/path/to/venv/bin/python3`.

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

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
search_sessions_toolA

Search session summaries in the activity database. Use for: broad time windows (yesterday, this week), daily/weekly overviews, what-did-I-work-on questions, project topics, task recaps. Returns paragraph summaries — NOT granular event detail. If the result says the info isn't there, call search_events_tool next. For exact date ranges prefer list_sessions_tool or search_bounded_tool.

search_events_toolA

Search individual events in the activity database. Use for: specific messages, OCR screen text, exact URLs, clipboard content, app usage, WhatsApp/email content, fine-grained timestamps, copy-paste history. Returns raw event rows with screen/OCR data. If the result says the info isn't there, call search_sessions_tool next. For exact date ranges prefer search_bounded_tool.

search_bounded_toolA

Keyword search with explicit time bounds (no LLM date guessing). start/end: epoch seconds or YYYY-MM-DD (local). table: 'events' or 'sessions'. Use when you know the calendar window and need pagination via limit/offset.

list_sessions_toolA

Chronological deduped session list for a time window. Prefer this over search_sessions_tool for day/week timelines. start/end: epoch or YYYY-MM-DD.

activity_coverage_toolB

Hourly (or custom) event-count buckets so capture gaps are honest. Empty buckets mean no events that hour — often capture was off. start required (epoch or YYYY-MM-DD); end defaults to now.

app_time_summary_toolB

Approximate per-app foreground time from event gaps in a window. start/end: epoch or YYYY-MM-DD. Durations are approximate (gaps capped at 5 min).

list_urls_toolB

Distinct URLs seen in active_url / OCR within a time window. pattern filters substring (e.g. 'greenhouse'). Deduped with counts.

list_screenshots_toolB

List screenshots (or OCR-backed stubs) in a time window. image_available=false means the JPEG expired; OCR preview may still be present.

get_screenshot_toolB

Fetch one screenshot by filename or unix timestamp. Returns redacted screen text. The image file path is not included. Screenshots use adaptive TTL (important frames kept longer, capped).

recall_memory_toolA

List long-term memory clusters ranked by freshness score. Pass query to run semantic recall instead of listing. Clusters below min_freshness are hidden unless include_stale=true.

fetch_cluster_toolA

Get all facts stored in a named memory cluster (with freshness annotations). Use after recall_memory_tool to get the full content of a specific topic. Pass the cluster label exactly as returned by recall_memory_tool.

save_identity_toolA

Save a personal fact about the user. op='set' for scalar facts (name, location, job). op='add_items' with items=[] for adding to a list (hobbies, skills). op='override' only when the user explicitly corrects a previous fact. op='remove_items' with items=[] to remove from a list.

remember_turn_toolA

Store durable facts from the user's own words. Call after the user tells you something about themselves, their preferences, relationships, plans, or anything they would want recalled later. Pass only the user's message, not your reply. Skip for activity questions, file search, and one-off tasks. Secrets, passwords, and API keys are not stored.

save_note_toolB

Save a free-form note or reminder the user wants remembered.

delete_note_toolA

Delete a note or memory fact the user wants forgotten. Use when the user says 'forget', 'delete', 'remove', or 'don't remember that'. Matches by substring — pass the key phrase or exact text from the note.

find_files_toolC

Search trusted workspace roots for a filename or substring.

list_workspace_roots_toolA

List folders Clippy may search with find_files_tool.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

B3.4/5.0

Scored across 17 tools

Disambiguation3/5

Several tools have overlapping search purposes: search_sessions_tool, search_events_tool, search_bounded_tool, and list_sessions_tool all query the activity database, and descriptions only partially disambiguate (e.g. 'if result says not there, call the other one'). Memory tools recall_memory_tool, fetch_cluster_tool, save_identity_tool, remember_turn_tool, save_note_tool, and delete_note_tool overlap around memory storage/retrieval.

Naming Consistency5/5

All 17 tools follow a consistent snake_case verb_noun or noun_verb pattern (get_screenshot_tool, recall_memory_tool, find_files_tool, list_urls_tool), with the uniform '_tool' suffix making the set predictably uniform.

Tool Count3/5

17 tools is on the heavy side for a screen/memory assistant, and several pairs (search_sessions vs list_sessions, search_events vs search_bounded) could likely be collapsed without losing capability.

Completeness4/5

The surface covers capture (screenshots), memory storage/retrieval, note lifecycle (save/delete), file search, and rich activity querying with coverage/app-time/URL listing. Minor gaps like note editing/updating or explicit screenshot deletion exist but agents can work around them.

Maintenance

ActivityActive
ResponsivenessWithin a week