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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. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnly, idempotent, non-destructive. The description adds valuable behavioral context: first measurement on new version can take 5-30s, partial failures degrade gracefully, and sources_failed lists timeouts. No contradiction 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 a single paragraph that efficiently conveys a lot of information without redundancy. It avoids fluff. Minor improvement could be bullet points or clearer separation of caveats, but it's well-structured for its length.

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 no output schema, the description enumerates the return fields (summary block, advisory details, links, alternative versions). It covers ecosystem scope, timing caveat, error handling, and partial failure behavior. For a composite tool of this complexity, the description is complete.

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 description coverage is 100% (both parameters described). The description adds that scoped packages are accepted and version defaults to latest, which is already in the schema. It does not add significant meaning beyond what the schema provides, so baseline 3 is appropriate.

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 performs a composite check for adding npm packages, fanning out across deps.dev and bundlephobia. It lists specific outputs (summary block, per-advisory detail, links, alternative versions), making the purpose unambiguous. None of the sibling tools overlap in function, so no confusion.

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?

Explicit usage guidance: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me".' It also specifies ecosystem scope (NPM only v1; others fall under deps.dev:version directly), which helps the agent decide when not to use this tool. Alternative is implied though not named.

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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Glama MCP Gateway

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TDQS

A3.9/5.0
Disambiguation2/5

Several tools are near-identical entry points: ask_pipeworx_beta explicitly matches ask_pipeworx exactly, ask_pipeworx_grounded only differs in grounded extraction, and deep_research overlaps with both. Company-research tools (entity_profile, compare_entities, recent_changes, validate_claim) and the Polymarket scanner family also have fuzzy boundaries despite long descriptions.

Naming Consistency3/5

All names are lowercase snake_case, which is a consistent base convention. However, the pattern mixes verb-first names (search_notices, get_notice, list_subscriptions), noun-first names (entity_profile, polymarket_edges, pipeworx_trending), and bare verbs (remember, recall, forget).

Tool Count2/5

At 36 tools, the server is well past the 25-tool threshold and feels like a platform dump rather than a scoped toolkit. Only about five tools actually serve the 'UK Contracts' name; the rest are general Pipeworx routing, Polymarket betting, memory, subscription, and AI-visibility utilities.

Completeness4/5

The UK procurement surface itself is solid: search_notices, recent_notices, and get_notice cover Contracts Finder, while find_a_tender_recent and find_a_tender_notice cover high-value Find a Tender notices. Minor gaps exist—notably no full-corpus keyword search for high-value Find a Tender notices, and Contracts Finder detail does not list documents—but agents can usually work around these.