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Glama

Zenodo

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 already indicate readOnly, openWorld, and idempotent hints. The description adds critical behavioral details: partial failures degrade gracefully, bundlephobia's first measurement can take 5-30s, and a `sources_failed` list indicates 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 relatively long but every sentence serves a purpose: composite nature, use cases, return fields, limitations, and fallback behavior. It is well-structured with clear sections, though slightly verbose in the return details.

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?

With no output schema, the description thoroughly explains the return structure (summary block, advisories, links, alternative versions) and covers edge cases like partial failures and ecosystem restrictions. No gaps remain.

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 coverage is 100%, so baseline is 3. The description adds extra meaning: scoped packages (e.g., '@types/node') are accepted, and version defaults to latest when omitted. This adds moderate 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 explicitly states the tool's composite purpose: checking npm packages for license, advisories, version history, and bundle size in one call. It clearly distinguishes from sibling tools by focusing on npm dependency analysis.

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 provides explicit when-to-use guidance: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me"'. It also notes ecosystem limitations ('NPM ecosystem only in v1') and directs users to deps.dev:version for other package ecosystems.

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

All Zenodo toolsInspect
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TDQS

A3.5/5.0
Disambiguation2/5

Multiple tools have unclear boundaries: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, while ask_pipeworx, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all overlap in the 'how should I query data' space. Additionally, the tool set mixes two unrelated domains (Zenodo and Pipeworx) without any organizing principle, forcing agents to guess which family applies.

Naming Consistency2/5

All names are lowercase snake_case, but the semantic patterns are inconsistent: bare nouns for Zenodo tools (search, record, communities), product-prefixed names (pipeworx_*, polymarket_*), generic verbs (remember, forget, recall), and verb_noun compounds (list_subscriptions, generate_llms_txt). The server is named Zenodo, yet most tools carry a pipeworx or polymarket prefix, making the naming feel arbitrary relative to the server's identity.

Tool Count2/5

36 tools is excessive for a server whose stated identity is Zenodo; only 5 of the 36 tools actually relate to Zenodo, with the remaining 31 belonging to a separate Pipeworx data platform. This suggests a bundled or mislabeled server rather than a deliberately scoped tool surface, and even the Zenodo subset alone would be thin.

Completeness2/5

For the Zenodo domain implied by the server name, the surface is severely incomplete: it covers search and read/retrieval (search, record, record_files, communities, community_records) but entirely omits the deposit workflow that is central to Zenodo — no create, update, delete, versioning, or file upload/download tools. The unrelated Pipeworx side is over-built, but the actual Zenodo use case leaves agents with dead ends.

Resources