Skip to main content
Glama

Malwarebazaar

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.

TDQS

A4.8/5.0
Behavior5/5

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

Discloses partial failures, bundlephobia measurement delay (5-30s), and sources_failed behavior. Annotations already provide readOnlyHint, but description adds valuable operational context.

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?

Dense but well-structured; front-loads purpose and usage. Could be slightly trimmed but uses every sentence to add value.

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?

Describes return format (summary block, advisories, links, alternatives) despite no output schema. Covers error handling and performance characteristics.

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; description adds that scoped packages are accepted and version defaults to latest, providing extra clarity beyond schema properties.

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?

Clearly states composite check for npm packages, combining deps.dev and bundlephobia data. Specifies ecosystem (npm only) and distinguishes from sibling tools like ask_pipeworx or deep_research.

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 says when to use: when agent asks about safety, popularity, size. Also notes alternatives for non-npm ecosystems via deps.dev:version.

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

All Malwarebazaar 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

A3.5/5.0
Disambiguation2/5

Several tools are near-duplicates: ask_pipeworx_beta is described as currently identical to ask_pipeworx, and ask_pipeworx_grounded is the same router with extra verification. Malware sample searches also overlap across search_family, search_tag, search_signature, and recent_samples, while ai_visibility_check is wrapped by scan_competitor_ai_presence.

Naming Consistency3/5

The set mostly uses snake_case and verb-first names like get_sample_info and validate_claim, which is helpful. However, conventions are mixed across ask_pipeworx*, polymarket_*, pipeworx_*, search_*, and noun-style names like recent_samples and entity_profile, so there is no single predictable pattern.

Tool Count2/5

36 tools is already over the comfortable range, but the bigger issue is that the server is named Malwarebazaar while only about five tools actually deal with malware. The remaining tools belong to an unrelated data-research, prediction-market, memory, and subscription platform, making the count inappropriate for the server's apparent purpose.

Completeness2/5

For the MalwareBazaar domain, the set covers metadata lookups and filtered sample searches but lacks sample submission, retrieval, or deeper analysis workflow. The rest of the tool surface targets unrelated domains, so there is no coherent, complete lifecycle for either malware intelligence or the broader feature set.

Resources