EnergiMCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| BASE_URL | No | Base URL for the hosted server; auto-detected from RAILWAY_PUBLIC_DOMAIN if not set. | |
| CACHE_DIR | No | Directory to keep the catalogue warm across restarts (the only volume worth mounting). |
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": true
} |
| prompts | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_datasetsA | Search the Energi Data Service catalogue (100 datasets covering Danish electricity, gas and grid data). Returns dataset names and titles; call describe_dataset before querying one. Discontinued datasets are hidden unless asked for. |
| describe_datasetA | Full metadata for one dataset: every column with type and unit, the time column that start/end filter on, the resolution, the update frequency, and the first and last timestamp that actually exist. Call this before query_dataset — column names cannot be guessed and the coverage window is different for every dataset. |
| query_datasetA | Fetch rows from any dataset. start/end filter on the dataset's own time column (see describe_dataset). Keep results small: name the columns you need, and use summary=true to get per-column statistics instead of rows when the range is long. Amounts and units are whatever the dataset documents; this tool does not convert them. |
| download_urlA | A URL that returns the whole result as CSV, JSON or Excel, for extracts too large to pass through a conversation. Nothing is fetched or rate-limited here; give the URL to the user or to a shell. |
| get_electricity_pricesA | Day-ahead electricity spot prices in 15-minute resolution, with the cheapest and most expensive periods worked out. Covers today and, once published in the early afternoon, tomorrow. Prices are per MWh excluding tariffs, taxes and VAT — a household bill is roughly double this. |
| get_carbon_intensityA | Grams of CO2 per kWh on the Danish grid, in 5-minute resolution, with an optional forecast. Use it to answer when to run something power-hungry. Returns the latest reading, the range over the window, and the greenest upcoming period when the forecast is included. |
| get_power_system_nowA | A one-minute snapshot of the Danish power system: production by source, wind and solar output, carbon intensity, and the flow on every interconnector. Positive exchange values are imports into Denmark; production plus net import equals consumption. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| when-to-run | Pick the cheapest or greenest window in the next day or two for something power-hungry: the dishwasher, the car, a heat pump, a compute job. |
| find-dataset | Work out which of the 100 datasets answers a question, and what it would take to query it. |
| grid-snapshot | What the Danish power system is doing right now, in plain language. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 7 tools
The catalogue workflow tools (list_datasets, describe_dataset, query_dataset) and the three convenience getters are largely distinct, but query_dataset can in principle fetch data overlapping with get_electricity_prices, get_carbon_intensity, and get_power_system_now. That boundary is slightly ambiguous, though the specialized getters make the intended choice clear in most cases.
Most tool names follow a predictable verb_noun snake_case pattern: list_datasets, describe_dataset, query_dataset, get_electricity_prices. Minor inconsistencies include list_datasets being plural while describe_dataset/query_dataset are singular, and download_url being less verb-like than the other retrieval helpers.
Seven tools is a well-scoped set for this domain: three catalogue lifecycle tools, one export helper, and three high-value convenience queries. Each tool earns its place without redundancy or bloat.
The set covers the full read-only workflow: discover datasets, inspect metadata, query rows, and generate download URLs for large exports. It also anticipates common user questions with electricity prices, carbon intensity, and power system snapshots, while query_dataset covers anything else in the catalogue.