ChargingNear.me

State charging statistics

get_state_charging_stats

Read-onlyIdempotent

Charging in one U.S. state: "how many EV chargers are in Colorado?", "which networks have the most chargers in Florida?". Send state: a two-letter code (CO), name (Colorado) or slug (colorado). Answers with the state's station count, DC fast and Level 2 counts, number of cities with charging, top networks and the state page link (url).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_state_charging_stats"
  }
}

Input Schema

Name	Required	Description	Default
`slug`	No	Same as state (kept for older calls)
`state`	No	State: two-letter code (CO), name (Colorado) or slug (colorado)

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedNov 9, 2026

changedInput schema / properties / slug / description

Previous value: -"State: two-letter abbreviation (CO), name (Colorado) or slug (colorado)"New value: +"Same as state (kept for older calls)"

addedInput schema / properties / state

Added value: +{
+  "description": "State: two-letter code (CO), name (Colorado) or slug (colorado)",
+  "type": "string"
+}

removedInput schema / required
```
Removed value: -[
-  "slug"
-]
```

First observedOct 25, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds value beyond that by specifying the exact response contents and the accepted input forms, though it says nothing about error behavior for invalid or ambiguous state values.

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?

The purpose and example queries are front-loaded, followed by the input format and then the return fields. Every sentence carries information an agent needs; there is no filler or repetition.

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 compensates by enumerating the returned fields, and it covers the input format for a tool with two optional parameters. Nothing essential for a correct read-only invocation is missing.

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

Parameters3/5

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

Schema coverage is 100%, so the accepted formats (code, name, slug) are already documented in the schema, and the description largely repeats them. It does not clarify the relationship between the two parameters, leaving the legacy 'slug' alias and any precedence between state and slug unaddressed.

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

Purpose4/5

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

The description names a specific resource (charging statistics for a single U.S. state) and enumerates exactly what comes back: station count, DC fast and Level 2 counts, cities with charging, top networks, and a state page URL. The scope word 'one U.S. state' implicitly separates it from get_city_charging_stats, but no sibling is named explicitly, so differentiation is left partly to inference.

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

Usage Guidelines4/5

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

Two concrete example questions ('how many EV chargers are in Colorado?', 'which networks have the most chargers in Florida?') give a clear picture of the request shape that should route here. It stops short of explicit exclusions or alternatives, so an agent must still infer that city-level counts belong to get_city_charging_stats.

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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