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Glama

Noaa Spc

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.

Schema Changelog

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

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

The description adds significant context beyond annotations: partial failures, bundlephobia timing out (5-30s), sources_failed list, and return structure. 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 front-loaded with the core purpose and contains valuable information, but it is somewhat dense. Every sentence earns its place, though it could be slightly more streamlined.

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?

No output schema, so description fully explains return values with a detailed list (summary block, advisories, links, alternatives). Also covers edge cases like partial failures and timeout behavior.

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 baseline is 3. The description mentions scoped packages are accepted and version defaults to latest, but these are already in the schema. No additional semantic value 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 deps.dev and bundlephobia. It precisely defines the tool's scope and distinguishes it from siblings, which focus on other topics.

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 says 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me".' Also notes NPM ecosystem only and directs to deps.dev for other ecosystems, providing clear when-to-use and alternatives.

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

B3.4/5.0
Disambiguation1/5

Several tools overlap heavily: ask_pipeworx and ask_pipeworx_beta are currently identical, and there are six polymarket_* tools plus bet_research for the same prediction-market domain. AI visibility and company profile tools also overlap, making selection genuinely ambiguous.

Naming Consistency3/5

All names are lowercase snake_case, which is consistent formatting, but the pattern is mixed: some are verb_noun (ask_pipeworx, generate_llms_txt, validate_claim) while many are noun-first (convective_outlook, polymarket_edges, entity_profile) or adjective-noun (recent_alerts, watches_active). It's readable but not a uniform verb_noun convention.

Tool Count2/5

35 tools is above the 25-tool threshold, and more importantly the set is bloated with a general-purpose research platform when the server is named Noaa Spc. Only 4 tools actually serve the SPC domain, so the count is inappropriate for the stated purpose.

Completeness3/5

For the dominant Pipeworx domain, the surface is fairly broad (query, compare, validate, subscribe, remember), but there are notable gaps: no update for subscriptions, no generic weather beyond SPC, and no direct list of all available sources. For the SPC purpose implied by the name, only 4 of 35 tools exist, so coverage is severely skewed.

Resources