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mcp-edf

mcp-edf

by mgcrea
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

EDF: Electricity Load Curve

edf_get_electricity_load_curve
Read-only

Retrieve Linky electricity load-curve data for a date range to see when power is drawn, including 30-minute or hourly kWh, average kW, range totals, and peak interval.

Instructions

The Linky load curve: energy per 30 minutes (or per hour) as compact rows of [start, kWh, average kW], with the range total and the peak interval. Use it to see when power is drawn (night vs day, a heater, a car charging); use edf_get_electricity_consumption for daily or monthly totals and costs. Paris local times. At most 7 days at 30m, 31 days at 1h, since a single day is 48 rows. The curve only exists if load-curve collection is switched on for the meter (it is on Suivi Conso's hourly view).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "from": "<from>"
    },
    "name": "edf_get_electricity_load_curve"
  }
}

Input Schema

NameRequiredDescriptionDefault
toNoLast day, INCLUSIVE, as YYYY-MM-DD, e.g. 2026-10-31. Defaults to yesterday: the meters report once a day, and a day's figures usually land the next morning around 08:00.
fromYesFirst day, inclusive, as YYYY-MM-DD in Paris time, e.g. 2026-10-01.
resolutionNo30m: the meter's native step (at most 7 days). 1h: hourly sums (at most 31 days).30m

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.7/5.0
Behavior4/5

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

Annotations only declare readOnlyHint and openWorldHint, so the description carries most of the load: it discloses timezone semantics (Paris local), hard range limits per resolution (7 days at 30m, 31 days at 1h), and the precondition that load-curve collection must be enabled for the meter. It does not cover failure behavior when data is missing or how partial days are handled, which keeps it short of a 5.

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

Conciseness5/5

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

Front-loads the return format, then the use case, the alternative tool, timezone, limits, and the availability precondition – each in a compact clause. No redundant or filler sentences.

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?

With no output schema, the description supplies the essential return shape (row tuple, range total, peak interval) and the data-availability caveat an agent needs to interpret empty results. Nothing critical for a correct call is missing.

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 coverage is 100% and already documents from/to/resolution well, so the baseline is 3. The description adds the coupling rationale ('a single day is 48 rows') and reiterates the per-resolution range caps, giving the agent a reason for the limits rather than just the numbers.

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?

Names a specific resource (Linky load curve) and states exactly what it returns: 30-minute or hourly energy rows of [start, kWh, average kW] plus range total and peak interval. It explicitly distinguishes itself from edf_get_electricity_consumption, which covers daily/monthly totals and costs.

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?

Gives a concrete when-to-use framing ('see when power is drawn – night vs day, a heater, a car charging') and names the sibling to use instead for daily/monthly totals. The resolution/range caps and the collection-enabled precondition further constrain correct usage.

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

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