Skip to main content
Glama

Check Dependencies

check_dependencies
Read-onlyIdempotent

Audit dependency packages (npm, PyPI, Maven, etc.) against CVE database to find known vulnerabilities. Supports bulk queries of up to 50 packages.

Instructions

Audit project dependencies (npm/PyPI/Maven/RubyGems/etc.) against CVE database: find known vulnerabilities in your package list. Bulk query up to 50 packages per call (same for Free and Pro). Use for dependency security scanning; use cve_lookup for single CVE. Free: 30/hr (1 per package), Pro: 500/hr. Returns {findings, total, by_severity, summary}. Each finding includes fixed_in (first patched version per NVD/MITRE version range) when a version range matched — omitted from wire when the range is open-ended or no input version was supplied; remediation copy then says 'Check if ... is affected ... and upgrade if so' instead of 'Upgrade to X.Y.Z or later'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packagesYesList of dependency packages to audit. Each item is an object with 'name' (required, max 200 chars, e.g. 'lodash', 'django', 'log4j-core') and optional 'version' (max 100 chars, e.g. '4.17.0', '2.14.1'). Only 'name' and 'version' fields are used; extra fields are ignored. Example: [{"name": "lodash", "version": "4.17.0"}, {"name": "django"}]. Maximum 50 per request (same cap for Free and Pro).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations indicate readOnly, idempotent, non-destructive. Description adds details on return structure {findings, total, by_severity, summary} and explains when fixed_in is omitted, providing behavioral context 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?

Description is somewhat long but well-structured: first sentence summarizes purpose, then provides usage, rate limits, return format, and special cases. Every sentence adds value, though slight trimming possible.

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 complexity of multiple package managers, bulk query limit, and return format, description covers all essential aspects including edge cases (open-ended version ranges). Output schema exists but description complements it.

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 coverage is 100% with detailed description of packages parameter. Description adds context on supported package managers (npm/PyPI etc.) and CVE database source, augmenting schema meaning.

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?

Description clearly states 'Audit project dependencies against CVE database: find known vulnerabilities in your package list.' It uses specific verbs and resources, and distinguishes from siblings like cve_lookup by specifying bulk query of packages.

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 'Use for dependency security scanning; use cve_lookup for single CVE.' Also provides rate limits for Free and Pro tiers, guiding appropriate usage.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/UPinar/contrastapi'

If you have feedback or need assistance with the MCP directory API, please join our Discord server