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Entur

by io.github.pipeworx-io

Entur Journey

entur_journey
Read-onlyIdempotent

Entur journey planner — plan a public-transport trip between any two places in Norway (Oslo to Bergen train, airport connections, city tram/metro/bus routes, ferries). Returns door-to-door itineraries with legs (mode, line, operator like Vy or Flytoget, aimed and expected times), total duration, transfer count, and walking distance. Example: entur_journey({ from: "Oslo S", to: "Bergen stasjon" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesDestination — place/station name or NSR id, e.g. "Bergen stasjon"
fromYesOrigin — place/station name or NSR id, e.g. "Oslo S"
modesNoOptional: restrict transit legs to these modes, e.g. ["rail"] for train-only
depart_atNoOptional departure time, ISO 8601 (e.g. "2026-07-20T08:00:00+02:00"). Default: now.
max_tripsNoMax itineraries to return, 1-10 (default 3)

TDQS

A4.3/5.0
Behavior4/5

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

The description adds behavioral detail beyond annotations by explaining the return structure (itineraries with legs, times, duration, etc.) and mentioning it is a planner (read-only, idempotent confirmed by annotations). It does not contradict annotations.

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 concise (two sentences plus an example) and front-loaded with the core purpose. Every sentence adds value without redundancy.

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

Completeness5/5

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

Given no output schema, the description adequately explains return values. It covers scope, required parameters via example, and optional ones. With 5 parameters and 100% schema coverage, the description is complete for selecting and invoking the tool.

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 includes an example that illustrates usage but does not add significant meaning beyond the schema's parameter descriptions.

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's purpose: planning public-transport trips in Norway. It specifies the verb 'plan', the resource 'public-transport trip', and the geographic scope. It also distinguishes from sibling tools like entur_departures and entur_stops_search by focusing on door-to-door itineraries.

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 usage context with examples and mentions specific scenarios (train, airport, city routes). However, it does not explicitly exclude use cases or name alternatives, which would enhance guidance.

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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TDQS

A3.7/5.0
Disambiguation2/5

Although many tools are individually well-described, there are several overlapping clusters: three ask_pipeworx variants, multiple polymarket edge/arbitrage tools, and AI-visibility checks vs their competitor-comparison wrapper. An agent can easily pick the wrong one because the boundaries (beta vs stable, grounded vs routed, edge vs arbitrage) are subtle despite the verbose descriptions.

Naming Consistency3/5

The set is consistently snake_case and mostly readable, so naming is not chaotic. However, the pattern is mixed: some tools use entur_/polymarket_/pipeworx_ prefixes, others are bare verbs (remember, recall, forget), and some are noun phrases (entity_profile, pipeworx_trending). The ask_pipeworx family also doesn't follow the pipeworx_ prefix convention used by neighboring tools.

Tool Count2/5

34 tools is well past the healthy range for a focused MCP server, and only three tools relate to the Entur transport domain implied by the server name. The other 31 tools form a separate, broad data/prediction-market product that appears bolted on, making the count inappropriate for the apparent purpose.

Completeness2/5

The Entur transport subset has stops search, departures, and journey planning, but misses common public-transport needs such as disruptions, service alerts, and fare/ticket information. The broader tool set is extensive but lacks a single coherent domain to be complete against, leaving the overall surface scattered and hard to trust as an integrated whole.

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