get_stationGet full detail for a single EV charging station by its Open Charge Map POI ID. Returns the connector types (CCS/CHAdeMO/Tesla connectors), charging speed (kW), operator, status, plus user comments and last-verified date.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Open Charge Map POI ID (e.g. from find_stations results). | |
| _apiKey | No | Optional — your own Open Charge Map API key for higher limits; works without one. |
Changes observed during successful MCP inspections.
Input schema / examplesPrevious value: -[
- {
- "_apiKey": "your-openchargemap-api-key",
- "id": 123456
- }
-]New value: +[
+ {
+ "id": 123456
+ }
+]Input schema / examplesAdded value: +[
+ {
+ "_apiKey": "your-openchargemap-api-key",
+ "id": 123456
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish the read-only, idempotent, non-destructive nature. The description adds useful behavioral context by listing the returned data (connector types, kW, operator, status, comments, last-verified date), which is especially valuable given there is no output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tight sentences with no filler. The first sentence front-loads the action and target, and the second efficiently lists the key result fields. Every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only retrieval tool, the description, schema, and annotations together give the agent everything needed to select and call it correctly. The returned-field list compensates for the missing output schema, and the optional API key is handled in the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters are already well documented. The description mainly restates the Open Charge Map POI ID concept and does not add new semantic detail beyond what the schema provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Uses a specific verb ('Get') and resource ('single EV charging station') qualified by a clear identifier ('Open Charge Map POI ID'). This clearly distinguishes it from the sibling find_stations tool, which implies searching/discovery rather than retrieving one known station.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the intended usage: call this when you already have a POI ID and need full station detail. The input schema reinforces this by noting the ID comes from find_stations results, but the description itself does not explicitly name alternatives or exclusions.
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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