Skip to main content
Glama

isochrone

Read-onlyIdempotent

Generate travel-time or travel-distance reachability polygons from an origin. Pass MULTIPLE bands in one call — e.g. contours_minutes:[10,20,30] returns three nested polygons in a single response (one round-trip, not three). Use for service coverage, dispatch range, territory design, 'how far can I get in X minutes' questions, and concentric zone visualizations. Output is GeoJSON ready for Mapbox / Leaflet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
costingNoTransport mode
locationYesCenter point address or 'lat,lon'
contours_kmNoDistance bands in km. Max 4 bands per call (over returns 400).
truck_heightNoTruck height in meters
truck_weightNoTruck weight in metric tons
contours_minutesNoTime bands in minutes, e.g. [10, 20, 30]. Max 4 bands per call (over returns 400).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsNo
geojsonNo
metricsNo
summaryNoMap of scalar facts the LLM should surface verbatim
display_hintNo

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, covering the safety and idempotency profile. The description adds meaningful behavior beyond annotations: multiple bands return nested polygons in a single response, and output is GeoJSON ready for Mapbox/Leaflet. This gives the agent useful operational context without contradicting annotations.

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 description is four sentences, each earning its place: core function, multi-band efficiency tip with example, intended use cases, and output format. It is front-loaded with the primary purpose and contains zero filler or redundancy.

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?

Given the presence of helpful annotations, an output schema, and full schema description coverage, the description supplies the essential extra context: clear use cases, multi-band round-trip optimization, and GeoJSON output. There is no need for it to restate parameter details or return value structure already captured elsewhere.

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 description coverage is 100%, so each parameter is already documented. The description supplements this with a concrete example (`contours_minutes:[10,20,30]`) and explains the efficiency advantage of multiple bands, which adds semantic value beyond the schema's basic descriptions. It doesn't explain the truck parameters, but the schema covers them adequately.

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?

The description opens with 'Generate travel-time or travel-distance reachability polygons from an origin,' which is a specific verb and resource. It clearly distinguishes this tool from siblings like directions or distance_matrix by focusing on reachability polygons, and reinforces with concrete use cases like 'service coverage' and 'territory design.'

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?

The description gives strong context for when to use the tool: 'Use for service coverage, dispatch range, territory design, how far can I get in X minutes questions, and concentric zone visualizations.' It also provides a practical efficiency tip about passing multiple bands in one call. However, it does not explicitly name alternative tools or when not to use it, so it doesn't earn a 5.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.4/5.0
Disambiguation5/5

Every tool has a clearly distinct purpose. Overlapping tools (geocode vs geocode_structured, explore vs search_places, map_match vs trace_attributes) are explicitly differentiated in their descriptions, with cross-references guiding correct selection. No two tools appear to do the same thing.

Naming Consistency4/5

Most tools follow a predictable verb_noun pattern (geocode, reverse_geocode, batch_geocode, search_places, resolve_intersection), but there are minor deviations: some tools use noun-only names (directions, traffic, weather) and a couple use noun_verb order (place_get, geofence_contains). This creates slight inconsistency but remains readable.

Tool Count4/5

At 19 tools, the set is slightly heavy but each tool earns its place by covering a distinct geospatial function. The breadth spans geocoding, routing, places, telematics, geofencing, traffic, weather, and account management, making the count reasonable for a comprehensive geo API.

Completeness5/5

The tool surface is remarkably complete for a geospatial server: forward, reverse, batch, structured, and intersection geocoding; routing, matrix, and isochrones; place search, exploration, and ID lookup; map matching, trace attributes, and point snapping; plus geofencing, traffic, weather, and quota management. No critical gaps or dead ends apparent.

Resources