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Package CVE Check

check
Read-onlyIdempotent

Check any package for known CVEs before installing, querying OSV.dev for vulnerability details, severity, and fix versions across multiple ecosystems.

Instructions

Check a specific package for known CVEs before installing.

    Queries OSV.dev for vulnerabilities in the given package. Use this
    before installing an MCP server or dependency to verify it is safe.

    Args:
        package: Package name with optional version, e.g. "express@4.18.2",
                 "@modelcontextprotocol/server-filesystem@2025.1.14",
                 or just "requests" (resolves @latest).
        ecosystem: Package ecosystem — "npm", "pypi", "go", "cargo",
                   "maven", "nuget", "rubygems", "composer", "swift",
                   "pub", "hex", "conda", "deb", "apk", or "rpm".
                   Defaults to "npm".

    Returns:
        JSON with package, version, ecosystem, vulnerability count,
        and vulnerability details (id, severity, cvss, fix version, summary).
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
offlineNoUse only the local advisory database. An explicit version is required; registry resolution and publication checks are disabled.
packageYesPackage name with optional version, e.g. 'express@4.18.2', '@modelcontextprotocol/server-filesystem@2025.1.14', or 'requests' (resolves @latest).
versionNoOptional package version when omitted from ``package`` (e.g. package='flask', version='0.12.2'). Prefer embedding in ``package`` as 'flask@0.12.2' or 'flask==0.12.2' when possible.
ecosystemNoPackage ecosystem: 'npm', 'pypi', 'go', 'cargo', 'maven', 'nuget', 'rubygems', 'composer', 'swift', 'pub', 'hex', 'conda', 'deb', 'apk', or 'rpm'.npm

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. Changed1 schema field changedv0.102.0
    • addedInput schema / properties / offline
      Added value: +{
      +  "default": false,
      +  "description": "Use only the local advisory database. An explicit version is required; registry resolution and publication checks are disabled.",
      +  "title": "Offline",
      +  "type": "boolean"
      +}
  2. Changed1 schema field changedv0.93.0
    • addedInput schema / properties / version
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "description": "Optional package version when omitted from ``package`` (e.g. package='flask', version='0.12.2'). Prefer embedding in ``package`` as 'flask@0.12.2' or 'flask==0.12.2' when possible.",
      +  "title": "Version"
      +}
  3. Addedv0.88.4
  4. Removedv0.88.1
  5. Addedv0.87.1
  6. Removedv0.87.0
  7. Changed1 schema field changedv0.85.0
    • addedInput schema / additionalProperties
      Added value: +false
  8. Addedv0.84.5

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, so the safety profile is covered structurally. The description adds genuine value by disclosing the external dependency on OSV.dev (an outbound network query) and documenting the JSON return shape. 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.

Conciseness4/5

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

The key purpose is front-loaded in the first line, followed by a tight context sentence and structured Args/Returns blocks. It earns its length with the OSV.dev source note, usage guidance, and return-format disclosure, with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given rich annotations, an output schema, and 100% parameter coverage, the description covers what matters beyond structure: external data source, when to invoke, and expected return fields. The only minor gap is that the offline/version parameters are not surfaced in the description text, though the schema fully documents them.

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 description coverage is 100%, so all four parameters are already documented structurally and the baseline is 3. The description reinforces package/ecosystem with concrete examples but omits the offline and version parameters entirely from its Args section. It adds convenience, not new meaning, on top of the 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 opens with a precise 'Check a specific package for known CVEs before installing' — a specific verb, resource, and scoping constraint. It clearly separates this single-package advisory check from broad siblings like scan or registry_lookup by framing it as a targeted, pre-installation safety verification.

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?

'Use this before installing an MCP server or dependency to verify it is safe' gives an explicit trigger condition and intended moment of use. However, it does not name any alternative tools or state when NOT to use it, leaving an agent to infer the boundary against scan/policy_check/marketplace_check on its own.

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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