Get pricing
hetzner_get_pricingFetch the full price list for the project's currency — server types, volumes, traffic, floating IPs, load balancers and backups. Hetzner Cloud: GET /pricing.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
hetzner_get_pricingFetch the full price list for the project's currency — server types, volumes, traffic, floating IPs, load balancers and backups. Hetzner Cloud: GET /pricing.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
readOnlyHint=true already tells the agent this is a safe read, so the bar is lower; the description adds genuine context beyond that by scoping the result to the project's currency and naming the six pricing categories returned. It does not mention VAT/tax treatment or whether prices are hourly vs monthly, which is the only real gap for a tool with 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 sentences, no filler: the scope and contents come first, the upstream API endpoint is a compact trailing reference. 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?
With no output schema, the description carries the burden of describing what comes back, and it does so by listing the priced categories. It falls just short of complete because it omits currency/VAT nuances and whether the payload is project-wide or location-dependent.
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?
The tool takes zero parameters, so per the rubric the baseline is 4. There is no parameter behavior to describe and the description correctly adds no noise about inputs.
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?
Specific verb ('Fetch') plus a precisely scoped resource ('the full price list for the project's currency'), and it enumerates the covered categories (server types, volumes, traffic, floating IPs, load balancers, backups). No sibling does anything similar, so it is unambiguously distinguishable from the list_*/get_* resource tools.
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 usage — call this when you need cost information for the project — but never states when to reach for it, whether it should be called before provisioning, or any caching/refresh guidance. With no competing pricing sibling, no exclusions are strictly needed, so this is adequate-but-implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.