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Glama

Opencages

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

A4.8/5.0
Behavior5/5

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

Annotations indicate read-only, idempotent, non-destructive, open-world. Description adds behavioral details: fans out across two services, returns specific summary fields, per-advisory detail, links, alternatives. Warns about bundlephobia latency and sources_failed field for timeouts.

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?

Description is informative but slightly lengthy; however, every sentence adds value. Front-loaded with core purpose.

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, but description fully explains return fields (summary block, per-advisory detail, links, alternatives) and handles partial failures. Covers input, output, behavior, and failure modes for a composite tool.

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. Description adds that scoped packages (@types/node) are accepted and that version defaults to latest published when omitted, which adds 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?

Clearly states it's a composite check for npm packages combining deps.dev and bundlephobia, with specific use case 'should I add this npm package to my project'. Distinguishes from siblings by noting NPM only in v1 and alternatives for other ecosystems.

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' and provides guidance on partial failures. Mentions ecosystem limitation and fallback to 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

A3.8/5.0
Disambiguation3/5

Several tools occupy adjacent territory—ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer natural-language questions, and the Polymarket family has five overlapping analysis tools. The descriptions do a decent job of differentiating them, but an agent could still plausibly select the wrong variant in a mixed workflow.

Naming Consistency3/5

Most names follow a readable lowercase snake_case style, and there are coherent families like ask_pipeworx_*, polymarket_*, and pipeworx_*. However, conventions are mixed across the set—some are verb_noun (list_subscriptions, resolve_entity), some are bare verbs (forget, recall, reverse), and some are noun-phrase-only (entity_profile, recent_alerts)—so no single predictable pattern governs the whole server.

Tool Count2/5

33 tools is well past the 25+ threshold for a heavy tool surface, even accounting for the broad data-domain ambitions of the server. Many of these tools are meta-tools or thin variants of one another, so the set feels larger than necessary and imposes meaningful selection cost on an agent.

Completeness4/5

The server covers its apparent domain thoroughly: querying, grounded verification, deep research, entity resolution, profiles, comparisons, change tracking, claim validation, memory, subscriptions, and prediction-market analytics are all represented. Minor gaps exist—such as no direct tool for retrieving a raw pipeworx:// citation record and no account/auth flow—but agents can generally complete core workflows without dead ends.

Resources