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toruproject

MapNetwork MCP Server

by toruproject

compute_route

Compute walking or driving routes between two locations. Returns ordered coordinates and resolved start/end points for direct map overlay and markers.

Instructions

Compute a walking or driving route between two locations.

Returns the route as an ordered list of coordinates, plus the resolved from/to locations. Pass the result directly to generate_map's route parameter to overlay it on a map image. Use from/to as markers in generate_map to place pins at the start and end points.

Typical flow:

  1. route = compute_route(from_location={"label": "A"}, to_location={"label": "B"})

  2. generate_map(route=route, markers=[route["from"], route["to"]], ...)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNowalking
to_locationYes
from_locationYes
Behavior4/5

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

With no annotations provided, the description carries the burden of explaining behavior. It discloses the return value (ordered list of coordinates, resolved from/to), notes compatibility with generate_map, and implies a pure computation with no side effects. This goes beyond basic 'computes a route' and covers the key operational aspects.

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 efficient: a clear first sentence, return-value summary, usage guidance, and a numbered example flow. Every sentence adds value, and the code snippet concretely demonstrates integration without unnecessary verbosity.

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 absence of output schema and annotations, the description adequately covers return structure and how to chain with generate_map. It could mention error behavior or mode values, but for a straightforward compute tool the provided information is sufficient for typical use.

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 description coverage is 0%, so the description must compensate. It illustrates usage with from_location/to_location objects and gives an example with 'label', but it does not explain the 'mode' parameter (walking/driving) or the nested 'location' structure. The example helps but does not fully cover all parameters.

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 'Compute a walking or driving route between two locations,' using a specific verb and resource. It distinguishes from siblings by covering route computation rather than map generation or status checks.

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 provides clear context on how to use the tool (pass result to generate_map, use from/to as markers) and gives a typical flow. It does not explicitly mention when not to use it or alternative tools, but the intended workflow is unambiguous.

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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