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Security Scan

scan
Read-onlyIdempotent

Discover local MCP configurations, extract package dependencies, query CVEs, assess config security, compute blast radius, and return a structured AI-BOM report with vulnerabilities and remediation guidance.

Instructions

Run a full AI supply chain security scan.

    Discovers local MCP configurations (Claude Desktop, Cursor, Windsurf,
    VS Code Copilot, OpenClaw, etc.), extracts package dependencies, queries
    OSV.dev for CVEs, assesses config security (credential exposure, tool access),
    computes blast radius, and returns structured results.

    Returns:
        JSON with the complete AI-BOM report including agents, packages,
        vulnerabilities, blast radius, and remediation guidance.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
config_pathNoPath to MCP client config directory. Auto-discovers all if omitted.
imageNoDocker image to scan (e.g. 'nginx:1.25', 'ghcr.io/org/app:v1').
sbom_pathNoPath to existing CycloneDX or SPDX JSON SBOM file to ingest.
enrichNoEnable NVD CVSS, EPSS probability, and CISA KEV enrichment.
offlineNoUse the local vulnerability DB only and skip registry, OSV, GHSA, and NVIDIA network lookups.
scorecardNoEnrich packages with OpenSSF Scorecard scores (requires resolvable GitHub repos).
transitiveNoResolve transitive dependencies for npx/uvx packages.
verify_integrityNoVerify package SHA-256/SRI hashes and SLSA provenance against registries.
fail_severityNoReturn failure status if vulns at this severity or higher: critical, high, medium, low.
warn_severityNoReturn warning status (gate_status=warn, exit 0) when vulns at this severity or higher exist. Use with fail_severity for two-tier CI gates, e.g. warn_severity='medium', fail_severity='critical'.
auto_update_dbNoExplicitly refresh the local vuln DB if stale (>7 days) before scanning.
db_sourcesNoComma-separated DB sources to sync before scanning (e.g. 'nvd,ghsa,osv,epss,kev').
output_formatNoOutput format: 'json' (default), 'sarif', 'cyclonedx', 'spdx', 'junit', 'csv', or 'markdown'.json
policyNoPolicy object to evaluate alongside scan results, e.g. {"rules": [{"id": "no-critical", "severity_gte": "critical", "action": "fail"}]}.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Beyond annotations (readOnly, idempotent, non-destructive), the description details specific behaviors: querying OSV.dev, assessing config security, computing blast radius, and returning AI-BOM reports.

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 front-loaded with a clear purpose and uses bullet points for key activities, but could be slightly more concise by trimming redundant phrasing.

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 14 optional parameters with full schema descriptions, an existing output schema, and detailed annotations, the description provides sufficient context for the tool's use without needing to restate structured data.

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?

With 100% schema description coverage, the description adds minimal parameter information beyond the schema's own descriptions; baseline 3 is appropriate.

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 'Run a full AI supply chain security scan' and lists specific scanning activities and outputs, distinguishing it from more focused sibling tools like code_scan or model_file_scan.

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?

The description implies this is the comprehensive scan, but lacks explicit guidance on when to use it vs. its siblings (e.g., 'for a full scan, use scan; for code-specific, use code_scan').

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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