update_lesson_completion

Mark a lesson as complete/incomplete for a student

SERVERGoHighLevel MCP Server SOURCEbusybee3333/go-high-level-mcp-2026-complete

Medium RISK CLASS

Category Write

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/busybee3333-go-high-level-mcp-2026-complete/update-lesson-completion.md

WHAT IT DOES

What update_lesson_completion does on GoHighLevel MCP Server

AI agents use update_lesson_completion to create or update resources in GoHighLevel MCP Server, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your GoHighLevel MCP Server environment.

RISK

Why update_lesson_completion is rated Medium

This tool creates or modifies student data (lesson completion status) in a reversible manner. The action can be toggled (complete/incomplete), so it is not destructive. While it affects educational records, it does not execute arbitrary code, delete data irreversibly, or move money.

From the tool's definition Tool name 'update_lesson_completion' and description 'Mark a lesson as complete/incomplete for a student' indicate modification of student progress records.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs update_lesson_completion safely

PolicyLayer is an MCP gateway: it sits between your AI agents and GoHighLevel MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For update_lesson_completion, this is the rule to start with:

update_lesson_completion Rate-limited

update_lesson_completion stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "update_lesson_completion": {
      "limits": [
        {
          "counter": "update_lesson_completion_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect GoHighLevel MCP Server, apply this rule, and every update_lesson_completion call is checked against it from then on.

FAQ

Questions about update_lesson_completion

What does the update_lesson_completion tool do? +

Mark a lesson as complete/incomplete for a student. It is categorised as a Write tool in the GoHighLevel MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on update_lesson_completion? +

Register the GoHighLevel MCP Server MCP server in PolicyLayer and add a rule for update_lesson_completion: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches GoHighLevel MCP Server. Nothing to install.

What risk level is update_lesson_completion? +

update_lesson_completion is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit update_lesson_completion? +

Yes. Add a rate_limit block to the update_lesson_completion rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block update_lesson_completion completely? +

Set action: deny in the PolicyLayer policy for update_lesson_completion. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides update_lesson_completion? +

update_lesson_completion is provided by the GoHighLevel MCP Server MCP server (busybee3333/go-high-level-mcp-2026-complete). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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