service_status
Check engine readiness, fixture versus planet data, freshness, and payment mode. Free; call before relying on query results.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Check engine readiness, fixture versus planet data, freshness, and payment mode. Free; call before relying on query results.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It discloses that the call is free and that it should precede dependent queries, which are meaningful behavioral traits. 'Check' conveys read-only intent without claiming side effects. It could add more details about response behavior, but for a simple status tool the disclosure is solid.
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?
The description is a single, scannable sentence. It front-loads the action and resource, then lists the key status dimensions, closing with the critical usage directive. Every clause earns its place with no redundancy.
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 zero-parameter tool with no output schema, the description communicates purpose, cost, and timing in a compact way. It does not spell out the response format, but the listed status categories imply what the agent will receive. This is nearly complete for the tool's simplicity, though a short note on return shape would make it fully self-contained.
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 has zero parameters, so parameter semantics are trivially satisfied. The description adds meaning about what the status covers without needing to explain parameters. Baseline 4 is appropriate for a parameterless tool.
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?
The description clearly states a specific verb ('Check') and a distinct resource (service status), enumerating concrete aspects it covers: engine readiness, fixture versus planet data, freshness, and payment mode. This distinguishes it from the sibling data-query tools without ambiguity.
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 provides explicit guidance on when to use the tool: 'call before relying on query results.' It also notes the tool is free, which is relevant for cost-sensitive agents. However, it does not explicitly name sibling alternatives or state when not to use this tool, so it falls just short of a 5.
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.
The tools are mostly distinct: basemap_catalog, elevation, and service_status each target unique resources, while find_features and overpass_query both touch OSM data but are differentiated by abstraction level (preset categories in a small bbox vs. raw Overpass QL). Agents could still hesitate between the two OSM search tools, so not a perfect 5.
All names are lowercase snake_case, but they don't follow a consistent verb_noun pattern: most are noun phrases (elevation, overpass_query, service_status) and only find_features uses a verb. This is readable but stylistically mixed.
Five tools is a well-scoped set for a geospatial API: catalog, elevation, feature search, raw Overpass query, and service status. Each tool has a clear role and none feel redundant or excessive.
The core read-only geospatial workflows are covered: discover basemaps, sample elevation, search OSM features, run arbitrary Overpass queries, and check data/service state. Minor gaps exist (e.g., no direct basemap tile fetching or geocoding/reverse-geocoding), but agents can work around these with Overpass and the catalog details.