Skip to main content
Glama

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.

Schema Changelog

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

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

Annotations declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds significant behavioral context: it fans out to two external sources, handles partial failures gracefully, and notes that bundlephobia's first measurement can take 5-30 seconds, with sources_failed listing timeouts. No contradictions with 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 fairly long but well-structured, starting with the tool's purpose, then usage guidance, output summary, ecosystem scope, and behavior notes. Every sentence adds value, though slightly more conciseness could be achieved without loss of clarity.

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?

Despite having no output schema, the description enumerates the return fields (summary block with is_latest, license, etc., per-advisory detail, links, and recent alternative versions). It also explains partial failures and that bundlephobia may time out. For a two-parameter tool, this is comprehensive.

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 coverage is 100% with both 'package' and 'version' having descriptions. The description adds that 'version defaults to the latest published version when omitted' and that scoped packages (e.g., '@types/node') are accepted for 'package'. This clarifies semantics 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 states it is a composite check for npm packages, combining license, advisories, version history, and bundle size info. It uses specific verbs ('fans out') and resources ('deps.dev', 'bundlephobia'), and distinguishes from sibling tools which focus on AI, search, or other domains.

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 explicitly says 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me"', providing clear usage context. It also notes the tool is NPM-only in v1, but does not explicitly state when not to use it or list alternative tools.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but the set includes three very similar `ask_pipeworx` variants that could cause confusion despite detailed descriptions. The Polymarket and memory tools are well-differentiated.

Naming Consistency3/5

Names follow a mix of patterns: some `verb_noun` (ask_pipeworx, compare_entities), some `noun_noun` (entity_profile, polymarket_arbitrage), and some standalone nouns (forget, recall). While readable, the inconsistency is notable.

Tool Count3/5

At 33 tools, the server is on the heavy side for typical MCP servers (3-15 ideal). However, the broad scope covering many data domains partially justifies the count.

Completeness4/5

The tool set covers a wide range of data access and analysis needs, including entity resolution, company profiles, betting analysis, subscriptions, and memory. Minor gaps exist (e.g., no direct tool for editing entities), but overall it's well-rounded.