Absorb LMS MCP Server and API by Cotlet

Deactivate user in Absorb LMS

absorb_lms_deactivate_user

Read-onlyIdempotent

Deactivate user in the user's own Absorb LMS account from ChatGPT, Claude or any AI agent. Returns how to do it in Absorb LMS step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Absorb LMS Cloud Browser. Absorb LMS's official API: Absorb LMS has an Integration API, a REST API with JSON for learners, courses, departments and grades, but it needs a private key tied to your portal that your Absorb account team provides, and your own code (checked 20 Oct 2026).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "absorb_lms_deactivate_user"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 9, 2026

TDQS

A3.9/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With readOnlyHint=true and destructiveHint=false already declared, the description usefully adds that the tool opens nothing by itself and only returns instructions, which is exactly the behavioral nuance an agent needs. It also discloses the prerequisite context around Absorb's Integration API and key provisioning. Minor gap: no detail on the shape of the returned steps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The critical clarification (returns steps, opens nothing) is front-loaded, which is good. However, the final sentence about Absorb's Integration API is a long run-on with a parenthetical date that adds context but costs readability, and the second sentence packs two ideas together.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a no-parameter, no-output-schema guide tool, the description covers what it does, what it does not do, and which follow-up tools to use. That is sufficient for an agent to call it correctly, with only the return format left implicit.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so the baseline applies and there is nothing for the description to disambiguate. The description correctly does not invent parameter guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the specific action and target (deactivate a user in the user's own Absorb LMS account) and immediately clarifies the actual mechanic: it returns step-by-step instructions rather than performing the action. This distinguishes it from siblings like absorb_lms_create_user, though the tool name itself is slightly misleading and only the body text corrects it.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives clear usage context: call this to get the steps, then execute them with the cotlet_browser_* tools in the Cloud Browser. It also explains why the official API path is not the default (private key, own code). It does not state when NOT to use this versus a direct API tool, which keeps it below a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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