AI agents use add_course_instructor 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.
This tool creates or modifies course instructor data by adding a new instructor relationship. It is a reversible write operation (the instructor could be removed later) that changes CRM/course management state without deleting data or executing arbitrary code.
From the tool's definition Tool name 'add_course_instructor' and description 'Add an instructor to a course' indicates creation/modification of course instructor assignments.
Documented attack patterns abuse exactly the kind of access add_course_instructor gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and GoHighLevel MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for add_course_instructor:
{
"version": "1",
"default": "deny",
"tools": {
"add_course_instructor": {
"limits": [
{
"counter": "add_course_instructor_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
} add_course_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.
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Add an instructor to a course. 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.
Register the GoHighLevel MCP Server MCP server in PolicyLayer and add a rule for add_course_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 GoHighLevel MCP Server. Nothing to install.
add_course_instructor is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the add_course_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.
Set action: deny in the PolicyLayer policy for add_course_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.
add_course_instructor 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.
Deterministic rules across all 566 GoHighLevel MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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566 GoHighLevel MCP Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.