TokLedger
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": false
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| tokledger_statsB | Aggregate totals from the local LLM inference ledger: request count, prompt/completion tokens, average TTFT, energy (kWh), local cost ($), cloud-equivalent cost ($), and percent saved vs cloud. |
| tokledger_recentB | The most recent N ledger records (newest first). |
| tokledger_model_breakdownB | Per-model rollup: requests, tokens, avg TTFT, local and cloud-equivalent cost. |
| tokledger_cloud_savingsB | Local vs cloud cost comparison: total local $, total cloud-equivalent $, savings $ and %. |
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 4 tools
Tools are mostly distinct: stats for aggregate metrics, recent for raw records, model_breakdown for per-model rollup, and cloud_savings for cost comparison. However, tokledger_stats already includes cloud-equivalent cost and percent saved, which overlaps with tokledger_cloud_savings, creating minor ambiguity for cost-focused queries.
All tool names share the 'tokledger_' prefix and use consistent snake_case noun phrases. While not verb_noun, the convention is uniform and predictable.
Four tools is well-scoped for a ledger analytics server, covering summary, recent records, per-model breakdown, and savings. Each tool has a clear role without redundancy.
Core analytical queries are covered, but the surface lacks filtering by date range or model, and no pagination for recent records. These are minor gaps that agents could work around by adjusting N or using aggregate stats.