agent-bom

Security scanner and graph for AI supply chain and infrastructure — agents, MCP, runtime, and blast radius.

CommunityOnlineNo sign-inGlobalFreeRead-only

What it can do

  • Scan: Run a full AI supply chain security scan and return an AI-BOM. Point it at a target with one of: • repo_url — a public git repo URL (cloned + scanned, no checkout) • config_path — a local projec
  • Check: 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.
  • Intel Lookup: Look up one advisory from the local threat-intel database.

What data it sees

Do you need an account

No: the server works without sign-in

Security scanner and graph for AI supply chain and infrastructure — agents, MCP, runtime, and blast radius.

How to connect

How to connect agent-bom to Claude

The server address to paste into Claude settings:

https://agent-bom--agentbom.run.tools

  1. Open Claude (claude.ai or the desktop app).
  2. Go to Settings → Connectors.
  3. Click Add custom connector.
  4. Paste the server address copied below into Remote MCP server URL and click Add.
  5. In a chat, click + → Connectors and switch the new connector on.

Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

Authorization

After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

How to connect agent-bom to ChatGPT

The server address to paste into ChatGPT settings:

https://agent-bom--agentbom.run.tools

  1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
  2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
  3. Open Settings → Connectors and click Create.
  4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
  5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
  6. In a new chat open + → Apps/Connectors and enable the connector.

OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

Authorization

On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

How to connect agent-bom to Cursor

The server address to paste into Cursor settings:

https://agent-bom--agentbom.run.tools

Fastest: click Open in Cursor below and confirm the prompt.

Manually:

  1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
  2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
  3. Save the file. The server appears in the MCP list; authorize it there if asked.

Authorization

If the service needs sign-in, an authorize button appears next to the server in the MCP list.

Server tool list (8)

Raw names from tools/list. Only developers need these.

scanRun a full AI supply chain security scan and return an AI-BOM. Point it at a target with one of: • repo_url — a public git repo URL (cloned + scanned, no checkout) • config_path — a local project / MCP-config directory • image — a Docker image • sbom_path — an existing CycloneDX/SPDX SBOM • package — a single package or MCP launch command (pair it with ``ecosystem`` when the spec names no launcher) With none of these, it auto-discovers local MCP clients (Claude Desktop, Cursor, Windsurf, VS Code Copilot, OpenClaw, etc.). It extracts package dependencies, queries OSV.dev for CVEs, assesses config security (credential exposure, tool access), computes blast radius, and returns structured results. Scanning is fully static and read-only — repository and image contents are parsed, never executed. Returns: JSON with the complete AI-BOM report including agents, packages, vulnerabilities, blast radius, and remediation guidance.
checkCheck 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).
intel_lookupLook up one advisory from the local threat-intel database.
exposure_pathsReturn ranked ExposurePath JSON for headless security agents. This is the agent-native graph surface: Claude, Cursor, Codex, Windsurf, Cortex, and other MCP clients can request the same investigation objects used by the dashboard without scraping UI state.
policy_checkEvaluate a security policy against current scan results. Runs a scan, then evaluates the provided policy rules against the findings. Policies can gate on severity thresholds, CISA KEV status, AI risk flags, credential exposure, and denied packages. Args: policy_json: JSON string containing policy rules. Example: {"rules": [{"id": "no-critical", "severity_gte": "critical", "action": "fail"}, {"id": "no-kev", "kev": true, "action": "fail"}]} Returns: JSON with passed (bool), violations list, failure_count, and warning_count.
generate_sbomGenerate a Software Bill of Materials (SBOM) for your AI agent setup. Discovers AI agents and MCP servers, extracts all package dependencies, and generates a standards-compliant SBOM. Args: format: SBOM format — "cyclonedx" (CycloneDX 1.7) or "spdx" (SPDX 3.0). config_path: Path to a specific MCP config directory. If not provided, auto-discovers all local agent configs. Returns: JSON string containing the SBOM in the requested format.
complianceGet OWASP LLM Top 10 / OWASP MCP Top 10 / MITRE ATLAS / NIST AI RMF compliance posture. Scans local MCP configurations, maps findings to 47 security controls across four AI security frameworks, and returns per-control pass/warning/fail status with an overall compliance score. Args: config_path: Path to a specific MCP config directory. If not provided, auto-discovers all local agent configs. image: Docker image reference to scan (e.g. "nginx:1.25"). Returns: JSON with overall_score (0-100), overall_status (pass/warning/fail/no_data), and per-control details for OWASP LLM Top 10 (10 controls), OWASP MCP Top 10 (10 controls), MITRE ATLAS (13 techniques), and NIST AI RMF (14 subcategories). Plus a nist_800_53_catalog line: the vendor-asserted, catalog-backed NIST SP 800-53 Rev 5 score over evaluated controls only (with ISO-27001-by-id attribution), scored independently and NOT folded into overall_score.
remediateGenerate a remediation plan for vulnerabilities in your AI agent setup. Scans for vulnerabilities, then generates actionable fix commands for each affected package (npm install, pip install), credential scope reduction guidance, and reports on unfixable vulnerabilities. Args: config_path: Path to a specific MCP config directory. If not provided, auto-discovers all local agent configs. image: Docker image reference to scan (e.g. "nginx:1.25"). Returns: JSON with package_fixes (upgrade commands by ecosystem), credential_fixes (scope reduction steps), and unfixable items.