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@kieksme/listmonk-mcp

@kieksme/listmonk-mcp

by kieksme

Get Server Config

listmonk_get_server_config
Read-onlyIdempotent

Retrieve a Listmonk instance's general settings—site name, languages, and permissions—to inspect configuration or verify admin defaults as markdown or JSON.

Instructions

Returns Listmonk's general server configuration (site name, languages, permissions, etc).

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": "listmonk_get_server_config"
  }
}

Input Schema

NameRequiredDescriptionDefault
response_formatNoOutput format: 'markdown' for human-readable text (default) or 'json' for machine-readable data.markdown

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.3.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive, and openWorld, so the safety profile is fully covered by structured data. The description adds the useful detail that the payload is static server-level config rather than user data, but says nothing about auth requirements, caching/staleness, or whether any fields are sensitive (permissions are exposed).

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

Conciseness4/5

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

One front-loaded sentence with no filler, which is the right shape for a simple getter. The trailing "etc" slightly undercuts it by hedging on what the payload contains rather than naming the remaining fields or omitting the list entirely.

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

Completeness3/5

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

For a zero-required-param read tool with no output schema, the definition is adequate but thin: it gestures at return contents with "etc" instead of describing the response shape, and gives no disambiguation from `listmonk_get_settings`. Nothing here would cause a misinvocation, but the definition leaves gaps an agent would have to probe to resolve.

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?

The single optional `response_format` parameter is fully documented in the schema with its enum and default, so the schema carries the semantics. The description adds nothing about the parameter, which is acceptable given 100% coverage, landing at the baseline.

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?

Uses a specific verb ("Returns") and a named resource ("Listmonk's general server configuration") and parenthetically enumerates the contents (site name, languages, permissions). It is clear on its own, but it never distinguishes itself from the sibling `listmonk_get_settings`, which an agent could reasonably confuse with server configuration.

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 call this versus `listmonk_get_settings`, `listmonk_get_health`, or `listmonk_get_dashboard_counts`, all of which are adjacent informational tools. No prerequisites, no exclusions, no context — the agent must infer usage entirely from the name.

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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