gql_mark_lesson_incomplete

Mark a lesson as incomplete for a user (GraphQL).

SERVERThinkific MCP Server SOURCEackbarguppi-ai/thinkific-mcp

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/ackbarguppi-ai-thinkific-mcp/gql-mark-lesson-incomplete.md

WHAT IT DOES

What gql_mark_lesson_incomplete does on Thinkific MCP Server

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

RISK

Why gql_mark_lesson_incomplete is rated Medium

This tool modifies user lesson completion state, which is data that can be reversed (mark back to complete). It does not delete data, execute arbitrary code, or involve financial transactions. The medium severity reflects that misuse could affect user progress tracking and course state, but the change is reversible and limited in scope to lesson completion status.

From the tool's definition Tool description states "Mark a lesson as incomplete for a user" - a modifying action that changes lesson completion state for a user record.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs gql_mark_lesson_incomplete safely

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

gql_mark_lesson_incomplete Rate-limited

gql_mark_lesson_incomplete 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": {
    "gql_mark_lesson_incomplete": {
      "limits": [
        {
          "counter": "gql_mark_lesson_incomplete_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 Thinkific MCP Server, apply this rule, and every gql_mark_lesson_incomplete call is checked against it from then on.

FAQ

Questions about gql_mark_lesson_incomplete

What does the gql_mark_lesson_incomplete tool do? +

Mark a lesson as incomplete for a user (GraphQL). It is categorised as a Write tool in the Thinkific 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 gql_mark_lesson_incomplete? +

Register the Thinkific MCP Server MCP server in PolicyLayer and add a rule for gql_mark_lesson_incomplete: 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 Thinkific MCP Server. Nothing to install.

What risk level is gql_mark_lesson_incomplete? +

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

Can I rate-limit gql_mark_lesson_incomplete? +

Yes. Add a rate_limit block to the gql_mark_lesson_incomplete 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 gql_mark_lesson_incomplete completely? +

Set action: deny in the PolicyLayer policy for gql_mark_lesson_incomplete. 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 gql_mark_lesson_incomplete? +

gql_mark_lesson_incomplete is provided by the Thinkific MCP Server MCP server (ackbarguppi-ai/thinkific-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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