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toruproject

MapNetwork MCP Server

by toruproject

generate_route_map

Create a route map showing walking or driving directions between two places, with both endpoints pinned automatically for clear visual navigation.

Instructions

Compute a walking/driving route between two places and generate a map with it overlaid. Both endpoints are pinned on the map automatically — do not also call generate_markers_map for them.

Example: generate_route_map(from="Tokyo Station", to="Tokyo Tower", mode="walking")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesRoute end. Place name to geocode.
fromYesRoute start. Place name to geocode.
modeNoDefault 'walking'.walking
nameNoOptional: display name for the map. If omitted, the server derives one automatically from place/route.
placeNoOptional: place to center the map on. If omitted, the center is computed automatically from the route.

Schema Changelog

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

  1. Changed1 schema field changedv6.0.0
    • addedInput schema / properties / name
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "description": "Optional: display name for the map. If omitted, the server derives one automatically from place/route.",
      +  "title": "Name"
      +}
  2. Addedv5.0.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It honestly states that endpoints are pinned automatically and that calling generate_markers_map would be redundant. Still, it omits what the tool returns (e.g., a file path, image, or download URL) and possible side effects such as creating, overwriting, or storing a map.

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 two short sentences plus a compact example. The core purpose is front-loaded, the anti-redundancy warning is useful, and the example is illustrative without bloat. Every sentence earns its place.

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?

For a tool with five parameters, no output schema, and no annotations, the description covers the key usage context: what it computes, how endpoints behave, and the warning about the sibling tool. It lacks return-format or error-behavior details, but the example helps fill practical gaps. Minor incompleteness, so 4 rather than 5.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description does not add meaning beyond the schema; the example demonstrates the from/to/mode combination but does not clarify edge cases, default behaviors, or how the optional name/place interact with route generation. Thus it meets the baseline but doesn't exceed it.

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 specific verb+resource: compute a walking/driving route and generate a map with it overlaid. It also distinguishes itself from generate_markers_map by explicitly noting endpoints are pinned automatically, so the agent knows not to use that sibling.

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?

It provides explicit guidance on when to use this tool and notably includes a negative condition: 'do not also call generate_markers_map for them.' The example further clarifies invocation. However, it doesn't explicitly contrast with generate_map or explain when the generic map tool would be preferable, leaving some selection ambiguity.

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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