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lukleh

mcp-read-only-grafana

by lukleh

list_users

Retrieve all users in your Grafana organization with optional pagination and field selection for targeted data.

Instructions

List all users in the current organization.

Args: connection_name: Name of the Grafana connection page: Optional page number (1-indexed) per_page: Optional page size fields: Optional subset of Grafana org-user fields (for example: orgId,userId,avatarUrl,email,name,login,role,lastSeenAt,lastSeenAtAge,authLabels)

Returns: JSON string with list of users.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
fieldsNo
per_pageNo
connection_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observedv0.4.0

TDQS

A3.6/5.0
Behavior2/5

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

No annotations are provided, and the description does not disclose side effects, permissions, rate limits, or confirm read-only behavior beyond the verb 'List'. The absence of any transparency about potential impacts or access requirements leaves a gap for the agent.

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 concise and well-structured, with a short purpose statement followed by a clean list of parameters and a return note. No redundant or verbose content is present.

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 simple read-only listing operation, the description covers purpose, parameter meanings, and return format ('JSON string with list of users'). However, it omits details like error conditions, pagination behavior, or response structure, but these are not critical for such a basic tool.

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 description includes a brief explanation for each parameter (e.g., connection_name as 'Name of the Grafana connection', page as '1-indexed', per_page as 'page size', and fields with examples). This adds meaning beyond the bare schema, though it lacks details on defaults or constraints.

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 clearly states the action ('List') and the resource ('all users in the current organization'), making the tool's purpose unambiguous. It is distinct from sibling tools like list_teams or list_annotations, and the tool name reinforces this clarity.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives. While no direct sibling for listing users exists, the description does not mention any conditions, exclusions, or comparisons with other list operations, leaving the agent without explicit usage context.

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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