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Glama

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?

The description adds significant behavioral context beyond annotations: partial failures degrade gracefully, bundlephobia's first measurement can take 5-30 seconds, and sources_failed lists timeouts. Annotations already indicate read-only and idempotent, but the description enriches with real-world runtime behavior. No contradiction 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise yet comprehensive, front-loading the key composite check purpose. Every sentence adds value: ecosystem, return fields, delay warning, alternative for other ecosystems. No wasted words, and the structure is easy to scan.

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 complexity (composite of multiple sources), full schema coverage, and rich annotations, the description covers all necessary context: return fields, partial failure handling, timing, ecosystem scope. No output schema exists, but the description lists the returned fields explicitly, making it self-contained.

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% for both parameters (package and version). The description adds that version defaults to latest and accepts scoped packages (e.g., @types/node). This provides minimal added value beyond the schema, warranting a baseline score of 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 clearly states it performs a composite check for adding an npm package, covering license, advisories, version history, bundle size, and tree-shaking. It distinguishes itself from sibling tools by specifying the ecosystem (NPM) and referencing the underlying services (deps.dev, bundlephobia). This specificity ensures the agent understands the tool's unique purpose.

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 explicitly tells when to use: when an agent asks about package safety, popularity, or size, e.g., 'is X safe / popular / small' or 'what does adding lodash cost me'. It also notes limitations (NPM only) and directs to alternatives for other ecosystems (PyPI, Maven, Cargo, Go). This provides clear context for tool selection.

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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Glama MCP Gateway

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TDQS

A3.6/5.0
Disambiguation2/5

ask_pipeworx and ask_pipeworx_beta are explicitly described as functionally identical right now, creating direct ambiguity. The six polymarket tools (edges, arbitrage, edge_tracker, fill_risk, kalshi_spread, bet_research) have blurred boundaries for prediction-market tasks, and ai_visibility_check vs scan_competitor_ai_presence is a wrapper relationship. Only the memory trio and subscription lifecycle are cleanly distinct.

Naming Consistency2/5

Naming follows multiple conventions with no global pattern: bare verbs (remember, recall, forget, subscribe), product-prefixed verbs (ask_pipeworx, pipeworx_feedback), noun phrases (entity_profile, deep_research, recent_changes), and verb_noun snake_case (discover_tools, validate_claim). There are consistent pockets (the polymarket_* family, the TheGamesDB get_/list_/search_ verbs), but the overall mix across 35 tools is inconsistent.

Tool Count2/5

35 tools exceeds the 25-tool threshold for a heavy server, and the count is wildly disproportionate to the server's stated identity: only 4 of 35 tools relate to TheGamesDB while 31 belong to an unrelated Pipeworx data/prediction-market suite. The game database would justify roughly 5-10 tools, so the bulk of this surface is out of scope for the server name.

Completeness3/5

The Pipeworx portion is genuinely thorough — discovery, grounded querying, entity resolution, claim validation, subscription lifecycle, memory, and feedback form a coherent coverage. However, the namesake TheGamesDB surface is thin: search, get-by-id, list genres, and list platforms, with no games-by-platform/genre browsing, no media/screenshots beyond front boxart, and no updates feed. The set as a whole covers multiple unrelated domains with no single complete lifecycle.