update_instructor

Update an instructor

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/update-instructor.md

WHAT IT DOES

What update_instructor does on Thinkific MCP Server

AI agents use update_instructor 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 update_instructor is rated Medium

This tool modifies existing instructor information reversibly (update is not deletion or destruction). The blast radius is medium because unauthorized instructor updates could affect course delivery, student access, or permissions, but changes can be rolled back. It does not execute arbitrary code, delete data, or move money.

From the tool's definition Tool name is 'update_instructor' and description states 'Update an instructor' — indicates modification of instructor data/records.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs update_instructor 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 update_instructor, this is the rule to start with:

update_instructor Rate-limited

update_instructor 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_instructor": {
      "limits": [
        {
          "counter": "update_instructor_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 update_instructor call is checked against it from then on.

FAQ

Questions about update_instructor

What does the update_instructor tool do? +

Update an instructor. 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 update_instructor? +

Register the Thinkific MCP Server MCP server in PolicyLayer and add a rule for update_instructor: 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 update_instructor? +

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

Can I rate-limit update_instructor? +

Yes. Add a rate_limit block to the update_instructor 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_instructor completely? +

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

update_instructor 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.

KEEP EXPLORING

More on Thinkific MCP Server, and thousands of servers like it.

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aroflo_create_or_update_record on AroFlo MCP →team_manager_update_budget on Team Manager MCP → The MCP Attack Database →

Guides

Govern customer-ops agents →Argument validation →Scoped token →