Skip to main content
Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
CONTEXTBURN_BINNoPath to the contextburn CLI if not in ~/bin or the usual Homebrew paths.
CONTEXTBURN_LANGNoInterface language: en or ru. Alternatively set ~/.config/contextburn/lang.en
CONTEXTBURN_WARNNoTokens/hour that turns the menu-bar counter yellow.30000000
CONTEXTBURN_ALARMNoTokens/hour that turns it red.90000000
CONTEXTBURN_DAY_STARTNoHour your day starts — the daily total resets here.6

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
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
run_efficiencyB

Share of paid tokens that became model output versus re-reading of context already sent, over the last N hours of local Claude Code sessions. Reported by tokens and cost-weighted.

spend_breakdownB

Human-readable breakdown of token spend over the last N hours: run efficiency, sessions, and what specifically inflated the context.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

B3.2/5.0

Scored across 2 tools

Disambiguation3/5

Both tools report on token spend and efficiency over the last N hours, and spend_breakdown explicitly includes run efficiency, so their boundaries overlap. An agent could reasonably confuse which tool to call for a pure efficiency metric versus a full breakdown.

Naming Consistency4/5

Both tools use snake_case with descriptive two-word noun phrases, which is a predictable and consistent convention. However, run_efficiency is slightly less standard as a noun than spend_breakdown, and neither follows a verb_noun action pattern.

Tool Count3/5

Two tools is borderline thin for a server analyzing context burn. While each tool has a distinct output, the surface feels minimal and may lack supporting operations like listing sessions or filtering by project.

Completeness3/5

The tools cover efficiency metrics and a spend breakdown including sessions, but there is no tool to list sessions, drill into a specific session, or filter by project/model. Core reporting is present but not exhaustive, which could cause dead ends for deeper analysis.

Maintenance

ActivityMaintained
ResponsivenessNo issues