Check Point Management Write-Path MCP Server
Draft/publish/install access-rule lifecycle for compensating-control workflows -- the write path Check Point's official read-only MCP does not expose.
Baseline review at submission: an accuracy and overt-behavior check, not a full security audit, and it does not cover later changes to the repository. Learn more about our security review process.
Tools (4)
- checkpoint_list_access_rules
List current rules in an access layer
- checkpoint_add_access_rule
Add a rule in the current session (status: draft until published)
- checkpoint_publish_session
Commit drafted rules to the management server (draft to published)
- checkpoint_install_policy
Push published rules to gateways (published to installed -- the rule actually enforces)
An MCP server for Check Point Management write-path workflows: draft an access rule, publish the session, install policy — the full compensating-control lifecycle as typed MCP tools. Originally built for a live orchestration demo at Tenable EXPOSURE 2026 (Boston), where an AI agent deployed a compensating firewall control for an unpatchable industrial asset under human supervision.
What it does
Check Point’s official MCP bundle (@chkp/quantum-management-mcp) is read-only by design. But the classic vulnerability-management move for an asset you cannot patch — block traffic to it — needs add-access-rule, publish, and install-policy. This server fills that write-side gap with the three-stage lifecycle (draft → published → installed) matching the real Management API state machine, so an AI agent’s audit trail reads exactly like a human operator’s, and a supervising human gets two natural gates before anything enforces.
How it works
FastMCP v3 server whose tool surface mirrors Check Point’s Management API (add-access-rule, publish, install-policy, show-access-rulebase). The backend is deliberately in-memory — safe for demos, agent development, and workflow testing with zero credentials — and the interfaces are designed so the official cp_mgmt_api_python_sdk slots in for production against Smart-1 Cloud or on-prem without changing tool signatures or response shapes. All outputs are Markdown rule tables and lifecycle status summaries.