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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
ELECTRICITY_MAPS_API_TOKENNoOptional Electricity Maps API token for live, hourly grid-level carbon data. If not set, the server uses built-in annual averages.

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": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
list_regionsA

List the cloud regions Eco Router knows about, with the electricity grid zone each one draws power from.

rank_regionsA

Rank AWS, Google Cloud and Azure regions for a workload by the carbon intensity of their electricity grid, optionally balanced against estimated latency from an origin. Supports hard limits for allowed countries, maximum latency and maximum carbon intensity. Read notes before relying on close scores.

find_clean_windowA

For flexible batch jobs, find when in the next hours (up to 72) each candidate region's grid is forecast to be cleanest, and how much that saves compared with starting now. Local times default to this computer's time zone. Needs ELECTRICITY_MAPS_API_TOKEN with forecast access. Limit candidates with regions, providers or countries (at most 15 grid zones per call).

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A4.1/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a distinct purpose: listing known regions, ranking regions for a workload, and finding optimal start times for batch jobs. There is no overlap in what they return or when an agent would choose one over another.

Naming Consistency5/5

All three tool names follow a consistent verb_noun pattern: list_regions, rank_regions, find_clean_window. The verbs clearly indicate the action and the nouns indicate the object.

Tool Count4/5

Three tools is on the low end, but the server has a focused purpose: carbon-aware region selection. Each tool covers a distinct stage of that workflow, so the count feels appropriate rather than thin.

Completeness4/5

The tool surface covers the core workflow: discover regions, rank them for a workload, and find clean windows for flexible jobs. A minor gap is the lack of a tool to fetch detailed grid data for a single region, but agents can work around it with list_regions and rank_regions.

Maintenance

ActivityMaintained
ResponsivenessNo issues