Skip to main content
Glama

clear_usergroup

Destructive

Remove all members from a Slack usergroup by assigning a randomly selected deleted user, effectively clearing the group.

Instructions

Clear all users from a Slack usergroup.

Since Slack API doesn't support empty usergroups, this uses a workaround by setting the usergroup to contain only a randomly selected deleted user. This effectively clears the usergroup.

Args: usergroup_id: The usergroup ID (S...) to clear

Returns: True if usergroup was cleared successfully, False otherwise

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
usergroup_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A4.8/5.0
Behavior5/5

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

The description discloses the non-obvious workaround: the usergroup is set to contain only a randomly selected deleted user. This is meaningful behavioral context beyond the destructiveHint and readOnlyHint annotations, and it also documents the return behavior.

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

Conciseness5/5

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

The description is compact and well-structured: a clear one-line purpose, a brief workaround explanation, then Args and Returns sections. Every sentence earns its place with no filler.

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

Completeness5/5

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

For a simple one-parameter mutation tool, the description covers purpose, the reason for the workaround, the parameter semantics, and return values. Combined with the annotations, an agent has enough information to invoke and interpret the tool correctly.

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

Parameters5/5

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

The input schema provides no description, but the Args section fully explains the single parameter: 'the usergroup ID (S...) to clear.' This adds semantic meaning and a format hint that the schema lacks.

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

Purpose5/5

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

The description opens with a specific verb and resource: 'Clear all users from a Slack usergroup.' This clearly distinguishes the tool from siblings like update_usergroup_members, which manage membership rather than clear it entirely.

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?

The description explains the context and rationale for the tool: Slack API doesn't support empty usergroups, so this tool uses a workaround. This makes the intended use clear, though it does not explicitly name alternatives or state when not to use the tool.

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

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/redhat-community-ai-tools/slack-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server