Skip to main content
Glama
gridcarbon

gridcarbon-mcp

Official

List covered electricity zones

list_zones
Read-onlyIdempotent

Check if an electricity zone code is covered and list all supported zones. Shows data source, resolution, factor basis, and comparability for 45 grids across Europe, US, and Great Britain.

Instructions

List every electricity zone gridcarbon covers, with its upstream data source, its reporting resolution, and whether its numbers are comparable with the rest.

Call this whenever you are not certain a zone code exists. The data tools reject unknown codes on purpose — there is no sensible fallback, and substituting a neighbouring country's grid would be a fabrication.

Coverage is 45 zones: continental Europe + Nordics + Ireland (ENTSO-E), 10 US balancing authorities plus a Lower-48 aggregate (EIA), and Great Britain (NESO). There is NO coverage of Canada, Australia, Japan, China, India, Latin America or Africa.

This tool returns no measurements itself, but the values the other tools return follow one contract: the unit is gCO2eq/kWh and LOWER IS CLEANER; each value's "ts" is the START of its reporting interval in UTC; and "latest" means NEWEST PUBLISHED, NOT "now" — see typical_lag_hours below and always quote the timestamp with the number.

Two things this list tells you that matter for correctness:

  • factor_basis: "lifecycle" for 44 zones (IPCC AR5, includes construction and fuel supply chain) versus "operational" for GB (combustion only). GB values come from NESO and use OPERATIONAL (combustion-only) emission factors, not the IPCC AR5 lifecycle factors used for the other 44 zones. GB numbers are systematically lower and MUST NOT be compared or ranked against other zones.

  • typical_lag_hours: how far behind real time that source normally publishes. US zones are routinely ~1 day behind. This is normal, not an outage — but it means a US value must never be described as "right now".

Args:

  • source ("entsoe" | "eia" | "uk-neso", optional): filter by upstream provider.

  • search (string, optional): case-insensitive substring over zone code and name.

  • response_format ("markdown" | "json", default "markdown").

Returns (structured): { "count": 45, "total_covered": 45, "zones": [ { "zone": "DE", "name": "Germany-Luxembourg", "source": "entsoe", "resolution_min": 60, "factor_basis": "lifecycle", "typical_lag_hours": 4, "comparable_with_others": true }, { "zone": "GB", "name": "Great Britain", "source": "uk-neso", "resolution_min": 30, "factor_basis": "operational", "typical_lag_hours": 2, "comparable_with_others": false } ], "history_starts_at": "2026-08-21T00:00:00Z", "notes": [...] }

Examples:

  • "Which US grids do you cover?" -> source="eia"

  • "Do you have Italy?" -> search="italy" (returns the 7 Italian bidding zones)

  • "Is Japan supported?" -> search="japan" returns zero rows; say it is not covered.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
searchNoCase-insensitive substring filter over the zone code and the zone name, e.g. 'italy', 'NO-', 'iso'.
sourceNoOnly return zones from this upstream source. 'entsoe' = Europe, 'eia' = United States, 'uk-neso' = Great Britain.
response_formatNoOutput format for the text content. 'markdown' is compact and human-readable; 'json' returns the full structured payload as text. Structured data is always returned alongside either way.markdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYes
notesYes
zonesYes
total_coveredYes
history_starts_atYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, and openWorld hints, and the description adds substantial behavioral context beyond them: the gCO2eq/kWh unit contract, 'latest' means newest published not 'now', typical_lag_hours semantics, and the lifecycle-vs-operational factor_basis distinction. It also warns that GB numbers must not be ranked against the other 44 zones, which is critical correctness information.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but well-organized, front-loading the core purpose and then layering caveats and examples. Most sentences earn their place because they convey correctness-critical semantics. However, the GB operational-factor point is repeated in close proximity, so it could be tightened slightly without losing information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a discovery/registry tool with three optional parameters and an existing output schema, the description is exceptionally complete. It covers coverage scope, unsupported regions, filter behavior, return contract, caveats about lag and factor_basis, and example invocations. An agent has everything needed to call this tool correctly and interpret its results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the structured definitions already document all three parameters. The description adds value beyond the schema with usage examples, coverage mapping (entsoe/eia/uk-neso to regions), and the note that searching for an unsupported country returns zero rows and should be reported as not covered. This exceeds the baseline but is not exhaustive about edge-case behavior.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'List every electricity zone gridcarbon covers,' and enumerates the exact attributes returned (upstream data source, reporting resolution, comparability). It also disambiguates from the sibling measurement tools by explicitly stating 'This tool returns no measurements itself,' so an agent can distinguish it from get_carbon_intensity and get_intensity_history.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives an explicit trigger: 'Call this whenever you are not certain a zone code exists.' It explains why the data tools reject unknown codes and warns that substituting a neighboring country's grid would be a fabrication. It also gives concrete examples mapping user questions to filters, such as 'Which US grids do you cover?' -> source='eia'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.