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trondbjoroy

norway-location-transport-mcp

by trondbjoroy

Get live vehicle positions

get_vehicle_positions

Retrieve live positions of Norwegian public transport vehicles by operator codespace or line, with bearing, speed, and delay.

Instructions

Get live positions of public transport vehicles (Entur realtime), filtered by operator codespace and/or line. Each vehicle shows its position, bearing, speed, and delay. Codespace examples: ATB (Trondheim), KOL (Stavanger), SKY (Bergen area). Get a line_id from get_departures.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
line_idNoLine ID, e.g. 'ATB:Line:2_3'. Optional if codespace_id is given.
max_resultsNoMaximum number of vehicles to return
codespace_idNoOperator codespace, e.g. 'ATB'. Optional if line_id is given.

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description must carry the behavioral burden. It discloses that each vehicle shows position, bearing, speed, and delay, which is useful. However, it does not describe behavior when both or neither filter is provided, whether the call is read-only, or any rate limits. This is a partial disclosure but lacks completeness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise—three sentences—and front-loads the core purpose immediately. It avoids unnecessary verbosity while including practical examples. The structure flows logically from purpose to filtering details to param acquisition hint.

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 no annotations or output schema, the description covers essential aspects: purpose, filtering options, examples, and how to get a line_id. Gaps include unspecified behavior when parameters are omitted, but the given information is sufficient for an agent to make a correct initial call. Given the moderate complexity, this is 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 description coverage is 100%, so parameters are already documented. The description adds value by explaining the relationship between line_id and codespace_id ('and/or'), providing concrete examples for codespace (ATB, KOL, SKY), and indicating how to obtain line_id from get_departures. This goes beyond the schema and helps the agent construct valid calls.

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 gets live vehicle positions in real-time, specifies it is filtered by codespace and/or line, and distinguishes it from sibling tools like get_departures by focusing on positions rather than schedules. The verb 'Get' and resource 'live positions of public transport vehicles' are specific and unambiguous.

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 provides context on how to obtain a line_id via get_departures and gives example codespaces, but it does not explicitly state when to prefer this tool over alternatives (e.g., for real-time vehicle tracking vs. departures), nor does it specify exclusions or fallback conditions. Usage guidance is implied rather than explicit.

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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