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atlassian-browser-mcp

atlassian-browser-mcp

by GeiserX
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Search User

confluence_search_user
Read-onlyIdempotent

Find Confluence users by CQL query on Cloud or by group membership on Server/DC, returning matching users up to a configurable limit.

Instructions

Search Confluence users using CQL (Cloud) or group member API (Server/DC).

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of results (1-50)
queryYesSearch query - a CQL query string for user search. Examples of CQL: - Basic user lookup by full name: 'user.fullname ~ "First Last"' Note: Special identifiers need proper quoting in CQL: personal space keys (e.g., "~username"), reserved words, numeric IDs, and identifiers with special characters.
group_nameNoGroup to search within on Server/DC instances (default: 'confluence-users'). Ignored on Cloud.confluence-users

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.4.1
    • addedInput schema / additionalProperties
      Added value: +false
    • removedOutput schema / description
      Removed value: -"Generic wrapper for non-object return types."
  2. Addedv1.0.1

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive, and open-world behavior, so the description need not repeat those. It adds value by disclosing the dual API approach (CQL vs group member API), which affects how the tool behaves across deployments.

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?

A single, front-loaded sentence with no filler. Every part of the sentence conveys necessary information about the tool's operation.

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?

Given the output schema and annotations, the description covers the essential platform-specific behavior. It could mention that query is the primary parameter but the schema already does; overall it is adequately complete for a read-only search tool.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all three parameters, including the Cloud/Server distinction for group_name. The description adds no parameter-level meaning beyond mentioning CQL and group member API, which is already reflected in the schema.

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?

States a specific verb (Search) and resource (Confluence users), and explicitly distinguishes the backend approach (CQL for Cloud vs group member API for Server/DC). This clearly separates it from other Confluence tools that handle pages, comments, or spaces.

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?

Provides context for platform-specific invocation (Cloud vs Server/DC), which guides the agent on which parameters matter. However, it does not explicitly state when to prefer this over alternatives (such as jira_search_assignable_users) or exclusions.

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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