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Security Scan

scan
Read-onlyIdempotent

Run an AI supply chain security scan that discovers MCP configurations, extracts dependencies, detects vulnerabilities, assesses credential exposure, and computes blast radius for actionable remediation.

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.
packageNoDirect package or MCP launch command to scan, e.g. 'npx @modelcontextprotocol/server-filesystem@2025.1.14' or '@modelcontextprotocol/server-filesystem'.
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 when older than the daily freshness target 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
Behavior4/5

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

Annotations already indicate safe read behavior (readOnlyHint=true, idempotentHint=true). The description adds value by detailing external network queries (OSV.dev), local file discovery, and DB updates, which are not obvious from annotations alone.

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?

The description is front-loaded with the core purpose and structured as a single paragraph with clear bullet points. Every sentence adds value without redundancy.

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 the 15 optional parameters and the presence of an output schema, the description adequately explains the overall output (JSON report with specific components). However, it could be more complete by noting that this is the go-to tool for a full supply chain scan versus using siblings for sub-scans.

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 each parameter is well-documented in the schema. The tool description adds no extra parameter context beyond what's already in the input schema, meeting the baseline expectation.

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 the tool runs a 'full AI supply chain security scan' and lists specific discovery actions (configs, dependencies, CVEs, config security, blast radius). This verb+resource combination distinguishes it from more targeted 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 Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. With 50+ sibling tools covering specific scan types, the description should include context like 'Use for comprehensive security audit; use specific scans for targeted checks'.

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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