Skip to main content
Glama

Serper

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

A4.9/5.0
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 concrete behavioral details: composite fan-out, timing (bundlephobia first measurement 5-30s), graceful degradation via sources_failed. No contradictions.

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?

Single paragraph, front-loaded with the core purpose, followed by usage guidance, return summary, ecosystem scope, and edge cases. Every sentence adds value without redundancy.

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 two-parameter schema, no output schema, and read-only nature, the description thoroughly explains return structure (summary block, advisories, links, alternatives) and partial failure behavior. No missing critical information.

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 covers 100% of parameters with descriptions. The tool description adds a useful note about scoped packages (e.g., @types/node) and confirms default behavior for version. This exceeds the baseline of 3 by providing extra context beyond 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 clearly identifies the tool as a composite check for evaluating npm packages across deps.dev and bundlephobia, covering safety, popularity, and size. It distinguishes from siblings by specifying unique functionality not found in other tools.

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 states when to use (questions like 'is X safe / popular / small' or 'what does adding lodash cost me') and when not to (non-npm packages), directing to deps.dev directly for other ecosystems. Also mentions partial failure handling.

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

All Serper toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.9/5.0
Disambiguation3/5

The ask_pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research) has blurry boundaries — ask_pipeworx_beta is explicitly identical to ask_pipeworx today — and the six Polymarket tools (polymarket_arbitrage, polymarket_edges, polymarket_fill_risk, etc.) all operate in the opportunity-detection space. Extremely detailed descriptions help, but an agent could easily select the wrong variant.

Naming Consistency3/5

Snake_case is used throughout and the polymarket_* and pipeworx_* clusters are internally consistent, but the set mixes verb-first names (ask_pipeworx, resolve_entity, validate_claim) with noun-first names (entity_profile, recent_changes, news, places) roughly evenly. The 'beta' suffix on a stable production tool and the adjective-noun 'deep_research' add further inconsistency.

Tool Count2/5

At 34 tools this exceeds the 25+ threshold, and the count is padded with redundancy: three near-identical ask_pipeworx variants, ai_visibility_check wrapped by scan_competitor_ai_presence, and six overlapping Polymarket tools. The unusually broad multi-domain scope justifies more tools than a typical server, but several clusters could be consolidated.

Completeness4/5

The surface is thorough for a read-only data-access gateway: universal routing, grounded verification, entity resolution/profiles/comparisons, web/news/maps search, prediction-market analysis, memory CRUD, and a full subscription lifecycle. Minor gaps exist (no direct fetch tool for pipeworx:// citation URIs, no image/video Serper endpoints) but agents can work around them.

Resources