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by gemini2026
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

snyk_scan_library

Scan any library with Snyk to identify vulnerabilities, license issues, and get remediation advice across multiple ecosystems.

Instructions

Scan a library using Snyk for comprehensive security analysis.

Args:
    library_name: Name of the library to scan
    version: Version of the library (default: "latest")
    ecosystem: Package ecosystem ("pypi", "npm", "maven", etc.)

Returns:
    Detailed security report from Snyk including vulnerabilities, licenses, and remediation advice

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "library_name": "<library_name>"
    },
    "name": "snyk_scan_library"
  }
}

Input Schema

NameRequiredDescriptionDefault
versionNolatest
ecosystemNopypi
library_nameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.6.1
  2. Removedv1.9.0
  3. First observed

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description provides partial behavioral information: it scans a library and returns a detailed report. However, it lacks disclosure of side effects, rate limits, authentication requirements, or potential errors. The output description adds some transparency.

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 description is concise but includes a structured 'Args' section that is helpful. It front-loads the main purpose. Minor redundancy with the schema is acceptable given no schema descriptions.

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

Completeness2/5

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

While the description covers the tool's basic function and parameter semantics, it lacks context on prerequisites (e.g., Snyk account, API key), error handling, and usage constraints. The return summary is useful but incomplete for a security scanning tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description compensates for 0% schema coverage by listing each parameter with a brief description (e.g., ecosystem as 'pypi, npm, maven') and default values. This adds significant meaning beyond the schema's empty descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool scans a library using Snyk for security analysis, mentioning the return includes vulnerabilities, licenses, and remediation. However, given sibling tools like 'scan_library_vulnerabilities' and 'snyk_license_check', it could better differentiate the comprehensive scope of this tool.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool vs alternatives like 'snyk_scan_project' or 'snyk_license_check'. The description does not mention prerequisites or exclusions, leaving the agent to infer usage context.

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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