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Glama

Openrouteservice

by io.github.pipeworx-io

Isochrones

isochrones
Read-onlyIdempotent

"Reachable area in [N] minutes" / "drive-time / walk-time / bike-time polygons" / "service area" / "catchment polygon" / "isochrone map" — generate isochrone polygons (area reachable from a point in time or distance) for car / truck / bike / foot / wheelchair profiles using OpenStreetMap. Use for delivery zones, commute sheds, site selection.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rangeYesSeconds or meters.
profileNo
locationsYes
range_typeNotime (default) | distance

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "locations": [
+      [
+        8.681495,
+        49.41461
+      ]
+    ],
+    "profile": "walking",
+    "range": [
+      300,
+      600
+    ],
+    "range_type": "time"
+  },
+  {
+    "locations": [
+      [
+        2.352222,
+        48.856613
+      ]
+    ],
+    "range": [
+      1000,
+      2000
+    ],
+    "range_type": "distance"
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "description": "Isochrone response from OpenRouteService",
+  "type": "object"
+}
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds context about using OpenStreetMap data, which is helpful. No contradictions.

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 a single, front-loaded sentence with a list of alternative names and use cases. No wasted words; every part adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity and the presence of an output schema, the description covers core functionality, profiles, and use cases. Minor missing details (e.g., maximum range, location count limits) but still fairly complete.

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 coverage is 50%, but the description explicitly lists profiles (car, truck, bike, foot, wheelchair) and the concept of range in time/distance. This adds meaning beyond the schema, which lacks descriptions for profile and locations.

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 clearly states the tool generates isochrone polygons (area reachable from a point) for multiple profiles using OpenStreetMap. It provides alternative names and use cases, distinguishing it from sibling tools like directions or matrix.

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

Usage Guidelines3/5

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

The description mentions use cases but does not explicitly state when to use this tool vs alternatives. No exclusionary guidance is provided; usage is implied rather than stated.

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

All Openrouteservice toolsInspect
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TDQS

B3.2/5.0
Disambiguation1/5

The tool set is a chaotic mix of geographic routing, AI visibility, betting analysis, memory storage, and random utilities. Many tools overlap in purpose (e.g., multiple data lookup tools like ask_pipeworx, discover_tools, resolve_entity), and the domain is completely inconsistent, making it nearly impossible for an agent to distinguish which tool to use for a given task.

Naming Consistency1/5

Tool names follow no consistent pattern; they mix snake_case (ai_visibility_check, ask_pipeworx), camelCase (generate_llms_txt), and arbitrary verbs without a clear verb_noun structure. Some names are vague (processV2-like patterns are absent, but e.g., 'forget' is a single verb). This chaotic naming prevents an agent from predicting tool functions.

Tool Count1/5

With 27 tools covering routing, AI marketing, betting, memory, and more, the count is extremely mismatched for the server's implied purpose ('Openrouteservice'). Even ignoring the name, the number is high and the scope is far too broad, making the set unwieldy and unfocused.

Completeness1/5

No coherent domain can be inferred from the tool set; it is an arbitrary collection. The routing tools are present but overshadowed by unrelated tools. For any single domain (e.g., betting or routing), the surface is either incomplete or includes extraneous tools, leaving the set severely lacking a clear purpose.

Resources