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Query Package Vulnerabilities

osv.security.query
Read-onlyIdempotent

Check known vulnerabilities for any package version across 14+ ecosystems. Returns CVE/GHSA IDs and severity scores.

Instructions

Check known vulnerabilities for a specific package version in any ecosystem (npm, PyPI, Go, Maven, Rust, NuGet, 14+ more). Returns CVE/GHSA IDs, severity scores, and affected package counts. Powered by Google OSV.dev — aggregates GitHub Security Advisories, NVD, and ecosystem-native databases.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packageYesPackage name (e.g. lodash, requests, gin-gonic/gin)
versionYesPackage version to check (e.g. 4.17.20, 2.25.0)
ecosystemYesPackage ecosystem (npm, PyPI, Go, Maven, crates.io, NuGet, Packagist, RubyGems, etc.)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv1.5.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare safe read operations. The description adds value by specifying what results include (CVE/GHSA IDs, severity, counts) and data sources (OSV.dev, GitHub, NVD, etc.). 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?

Two concise sentences with no fluff. Front-loaded with purpose and key details. Every sentence earns its place.

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 full schema, output schema, and rich annotations, the description is complete. It explains purpose, output, and data sources. No major gaps for a single-package vulnerability check.

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 descriptions for each parameter. The description adds example values (lodash, 4.17.20) and mentions the wide ecosystem support (14+ more), which provides 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 states it checks vulnerabilities for a specific package version across many ecosystems, with specific output (CVE/GHSA IDs, severity, counts). It distinguishes from siblings like batch or get by specifying single package version.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Clearly states the tool is for checking vulnerabilities of a single package version. It does not explicitly mention when not to use it (e.g., bulk queries) or alternatives, but the context is clear enough given sibling names.

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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