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Entur

by io.github.pipeworx-io

Scan Dependency

scan_dependency
Read-onlyIdempotent

Composite "should I add this npm package to my project" check in ONE call — fans out across deps.dev (license + advisories + version history) and bundlephobia (gzipped/minified bundle size, dependency count, ESM/tree-shake support). Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me". Returns a summary block (is_latest, license, published_at, advisory_count, bundle_kb_min, bundle_kb_gz, dependency_count, has_esm, tree_shakeable), per-advisory detail, links, and a list of recent alternative versions. NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly. Partial failures degrade gracefully — bundlephobia's first measurement on a new version can take 5-30s; sources_failed will list it if it times out, the rest still returns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packageYesnpm package name. Scoped packages (e.g. "@types/node") are accepted.
versionNoSpecific version to check (e.g., "18.3.1"). Defaults to the latest published version when omitted.

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already show readOnly, openWorld, idempotent, non-destructive. The description adds crucial behavioral details: partial failures degrade gracefully, bundlephobia's first measurement may take 5-30s, sources_failed lists timeouts. This provides depth beyond annotations.

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 well-structured and front-loaded. It provides essential information without verbosity. Every sentence adds value, though it is somewhat lengthy for a concise tool description.

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 tool's complexity and lack of output schema, the description sufficiently explains the return format (summary block, per-advisory detail, links, alternatives). It covers failure modes and ecosystem scope. Minor gaps: does not specify exact fields in summary beyond listing them.

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 has 100% description coverage, so baseline is 3. Description adds value by clarifying that scoped packages are accepted and that version defaults to latest. This goes beyond the schema.

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 specifies the tool as a composite check for npm packages, covering license, advisories, bundle size, etc. It uses specific verbs and resource (scan dependency) and distinguishes from siblings by focusing on npm ecosystem.

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

Usage Guidelines5/5

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

Explicitly states when to use: when an agent asks about safety, popularity, size, or cost of adding a package. Also notes ecosystem scope (NPM only) and alternatives (deps.dev:version for other ecosystems).

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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