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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?

The description adds significant behavioral context beyond the annotations: it mentions partial failures degrade gracefully, that bundlephobia's first measurement can take 5-30s, and that sources_failed will list timeouts. It also discloses the composite fan-out nature, which is not captured by readOnly/idempotent hints.

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?

Though longer than many descriptions, every sentence earns its place: the opening defines the composite purpose, the second gives usage triggers, the third details return content, the fourth scopes the ecosystem, and the fifth addresses latency and failure handling. The structure is front-loaded with the core purpose and then flows logically.

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 the tool's complexity (composite of two services) and lack of an output schema, the description is remarkably complete. It specifies what is returned (summary block fields, per-advisory detail, links, alternative versions), the supported ecosystem, and graceful degradation behavior, leaving little ambiguity for an agent.

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?

The input schema has 100% parameter description coverage (package, version with defaults and scoped package note), so the baseline is 3. The tool description reinforces that 'package' is an npm package and that version defaults to latest, but does not add substantial new 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 opens with 'Composite "should I add this npm package to my project" check in ONE call', clearly identifying the tool's purpose as a single-call comprehensive scan of an npm package. It distinguishes from siblings like get_license by combining multiple sources (deps.dev, bundlephobia) and explicitly states it's a composite check.

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?

The description gives explicit usage guidance: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me"'. It also provides an exclusion and alternative: 'NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly', which helps an agent decide when not to use this tool.

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

A3.5/5.0
Disambiguation2/5

Many tools have overlapping purposes, such as multiple 'ask_pipeworx' variants, several company analysis tools, and multiple prediction market tools. The set is large and not well-disambiguated, leading to potential confusion.

Naming Consistency2/5

Naming conventions are mixed, with snake_case ('get_license'), camelCase ('ai_visibility_check'), and prefix-based ('pipeworx_*', 'polymarket_*'). No consistent pattern across the tool set.

Tool Count2/5

35 tools is excessive for a server named 'Spdx License', which implies a focused license management tool. The actual number is more appropriate for a general data platform, but mismatched with the server name.

Completeness1/5

For the implied SPDX license domain, only a few basic tools exist (list, get, search). Missing crucial features like create, update, delete, or compare licenses. The surface is severely incomplete for the stated purpose.