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Glama
tarhou

Check Point Management MCP Server

by tarhou
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}
logging
{}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
extensions
{
  "io.modelcontextprotocol/ui": {}
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
checkpoint_list_access_rulesA

List access rules in a given layer, optionally filtered by lifecycle status.

Mirrors the real Management API show-access-rulebase shape: each rule carries a uid, name, source/destination/service object lists, action, and a lifecycle status (draft/published/installed) reflecting where it sits in the publish + install-policy workflow.

checkpoint_add_access_ruleA

Add a new access rule to the current session.

The rule is created with status draft and is NOT committed or installed -- it lives in the current management session only. The orchestrator surfaces the draft to the operator for review, then calls checkpoint_publish_session and checkpoint_install_policy to move it through the lifecycle.

This is typically a human-gated step in a change workflow, reserved for network-policy changes.

checkpoint_publish_sessionA

Commit every drafted rule in the current session to the management server.

Drafted rules transition to published. Published rules survive across sessions but do NOT yet enforce on gateways -- that requires checkpoint_install_policy. Idempotent: calling with no drafts is a no-op.

checkpoint_install_policyA

Push published rules on a layer to the named gateways.

This is the moment a compensating-control rule actually starts blocking traffic on the wire. The orchestrator pairs this call with the operator's third human-in-loop approval.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.3/5.0

Scored across 4 tools

Disambiguation5/5

Each tool has a distinct and clearly defined purpose: listing rules, adding a draft rule, publishing the session, and installing the policy. There is no overlap or ambiguity between them.

Naming Consistency5/5

All tool names follow a consistent `checkpoint_<verb>_<noun>` pattern with clear and descriptive verbs (list, add, publish, install). The naming is uniform and predictable.

Tool Count4/5

Four tools is a reasonable scope for a focused policy management workflow. It covers the essential steps but could potentially include a few more without becoming overwhelming.

Completeness3/5

The tools cover the core lifecycle of creating, viewing, publishing, and installing access rules, but lack update and delete operations for individual rules. This may force agents to work around missing functionality.

Maintenance

ActivityStale
ResponsivenessNo issues

Resources