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Glama

Rcsb Pdb

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. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already mark this as read-only, open-world, idempotent, and non-destructive. The description adds meaningful behavioral context beyond annotations: composite fan-out, graceful partial failures, the 5-30s first-measurement latency on bundlephobia, and the sources_failed field indicating timeout behavior—none of which is visible from annotations alone.

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?

The description is front-loaded with the core value proposition, then usage guidance, return-format summary, ecosystem scope, and failure behavior—each sentence adds a distinct piece of information. No fluff or repetition of schema fields; despite its length, it's structurally tight.

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?

For a tool with no output schema, the description compensates thoroughly by enumerating the returned summary fields (is_latest, license, bundle_kb_gz, etc.), advisory details, links, and recent versions. It also covers the critical edge cases of ecosystem limitations and timeout behavior, making it fully actionable 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?

Input schema covers 100% of parameters with descriptions, including the default behavior of 'version'. The description reinforces the scope ('npm package name') and mentions output fields, but it doesn't add new syntactic or semantic detail beyond the schema; therefore it sits at the baseline 3.

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 a specific verb+resource ('Composite ... check in ONE call') and explicitly describes the fan-out across deps.dev and bundlephobia. It distinguishes itself from siblings by naming its composite nature and NPM ecosystem scope, making its purpose unambiguous.

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?

It provides explicit trigger phrasing: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me"'. It also sets boundaries by stating NPM-only and directing PyPI/Maven/Cargo/Go to deps.dev:version directly, effectively covering when not to use.

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

A3.7/5.0
Disambiguation2/5

ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are nearly identical in purpose, and structure/summary both fetch PDB entries. The server name 'Rcsb Pdb' doesn't match most tools, which are Pipeworx data tools, compounding ambiguity.

Naming Consistency3/5

Mostly snake_case verb_noun, but verbs are inconsistent (ask, discover, generate, list, recall) and some names are noun phrases (entity_profile, polymarket_edges). No clear pattern unifies the set.

Tool Count2/5

37 tools is excessive for a server ostensibly about RCSB PDB; only 6 tools relate to PDB while 31 serve unrelated Pipeworx functionality. The count feels like a bundled grab-bag rather than a focused toolset.

Completeness3/5

The PDB-specific tools cover the core operations (search, fetch, assembly, ligand, polymer entity), so the structural biology surface is mostly complete. However, the server's overall purpose is muddled, and the Pipeworx tools are a separate domain that happens to be bundled in, making it unclear what 'completeness' even means for this server.

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