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Glama

Figma

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

A4.6/5.0
Behavior5/5

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

Annotations already indicate readOnly, openWorld, idempotent, non-destructive. The description adds significant behavioral detail: fans out to external services, bundlephobia first measurement can take 5-30s, partial failures degrade gracefully with sources_failed reported. This enriches the agent's understanding beyond 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, well-structured paragraph. It front-loads the purpose, then covers use cases, limitations, and return value. While slightly verbose, every sentence earns its place. Minor improvement could be breaking into bullet points for return structure, but current form is still highly readable.

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?

Given the tool's complexity (composite check, multiple services, partial failures), the description is remarkably complete. Without an output schema, it details the return structure explicitly. It also covers timing, failure modes, and ecosystem scope. No external documentation is needed for basic understanding.

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% with clear descriptions for both parameters (package name with scoped packages, version with default). The description adds no additional meaning beyond what the schema already provides.

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 it's a composite check for npm packages, clearly distinguishing its purpose from sibling tools. It uses specific verbs ('check', 'fans out') and resources ('deps.dev', 'bundlephobia'). No sibling tool overlaps with this unique functionality.

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 ('is X safe / popular / small', 'what does adding lodash cost me'), notes ecosystem limitations (NPM only v1), and mentions alternative paths (PyPI/Maven etc. via deps.dev:version directly). It also warns about partial failures and timing.

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

A3.5/5.0
Disambiguation2/5

Many tools have overlapping purposes (e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded), and the set mixes Figma-specific tools with a large library of data-lookup tools, making it hard for an agent to distinguish when to use which.

Naming Consistency2/5

Naming conventions are inconsistent: snake_case (ask_pipeworx, deep_research), camelCase (get_me, get_file), and mixed underscores (list_comments). There is no consistent pattern across the tool set.

Tool Count1/5

The server is named 'Figma' but has 36 tools, only 5 of which are Figma-related. The remaining 31 are Pipeworx data tools, indicating a severe scope mismatch and unnecessary bloat for a Figma server.

Completeness1/5

The Figma-specific tools lack essential CRUD operations (e.g., no create, update, or delete for files or nodes). The Pipeworx tools, while extensive, are irrelevant to Figma, so the server is severely incomplete for its stated purpose.

Resources