tokenchit
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 | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_usageA | Total local AI coding agent usage: tokens, equivalent cost, streak, active days, per-agent mix and per-model breakdown. Windows are all time, the current calendar year so far, the last 30 days and the last 7 days. Reads logs on this machine; makes no network request. |
| get_daily_usageA | Tokens per local calendar day, most recent last. Use this for questions about a specific stretch of time rather than a lifetime total. |
| get_recapA | Year in review for one calendar year: headline tiles, per-agent and per-model breakdown, the busiest hour range, and activity aggregated by weekday and hour (not by date). The same figures |
| detect_agentsA | Which coding agents are installed on this machine, where each one's logs live, and whether they hold readable usage. Call this first when a usage read comes back empty. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
This server cannot be deployed
TDQS
Scored across 4 tools
get_usage (windowed totals), get_daily_usage (per-day series), and get_recap (year-in-review aggregates) have partially overlapping subject matter, but each description clearly states its scope and output shape. detect_agents is cleanly distinct. Minor risk that an agent asks for a time range and picks get_usage over get_daily_usage.
Three tools follow a clean get_<noun> snake_case pattern (get_usage, get_daily_usage, get_recap). detect_agents breaks the prefix convention slightly but is still snake_case and readable, so the set is nearly uniform.
Four focused tools cover the analytics surface without redundancy. It is on the lean side but each tool earns its place; nothing feels padded or missing at the count level.
Covers lifetime/window totals, daily series, yearly recap, and agent discovery/diagnostics, which addresses the core questions of a usage-tracking server. Possible gaps like per-project rollups or cross-agent comparison views are not indicated as supported, but no obvious dead end for the stated purpose.