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Estonian Transport MCP

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tallinn_vehicles

Track real-time GPS positions of Tallinn public transport vehicles. Filter live bus, tram, or trolleybus locations by line number for accurate arrival planning.

Instructions

Get real-time GPS positions of Tallinn public transport vehicles.

Args: vehicle_type: Filter by type: 'bus', 'tram', or 'trolleybus' (default: all) line: Filter by line/route number (e.g. '2', '17', '42A')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lineNo
vehicle_typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.4.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose that positions are real-time and that vehicle_type defaults to all, which is genuinely useful. However, it says nothing about data freshness, coordinate system, rate limits, or the shape of the response beyond what the output schema already covers.

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?

Front-loaded one-sentence purpose followed by a compact Args block; no filler. The args section is slightly schema-like but each line earns its place by adding undocumented filter semantics.

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?

With only two optional parameters, both documented, and an output schema present so return values need no explanation, the definition is nearly complete. Minor gaps remain regarding what the GPS payload contains (coordinates, vehicle IDs, timestamps), but the essentials for calling the tool are present.

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

Parameters5/5

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

Schema description coverage is 0%, and the description fully compensates: it names both parameters, enumerates the accepted vehicle_type values ('bus', 'tram', 'trolleybus'), states the default, and gives concrete line examples ('2', '17', '42A'). An agent can invoke this correctly without opening the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The first sentence states a specific verb and resource: 'Get real-time GPS positions of Tallinn public transport vehicles', including the city and the real-time qualifier. It is clear what the tool returns, though it does not distinguish itself from siblings like get_route or get_departures.

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

Usage Guidelines2/5

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

The description never says when to use this tool versus the many sibling tools (get_route, get_departures, search_stops). The filter documentation implies a lookup pattern, but no context, prerequisites, or alternatives are offered.

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