lmstudio

LM Studio: server status

server_status

Read-only

Check whether the LM Studio API is reachable and report the active URL, loaded models with TTL, and running background tasks; call this first to verify runtime status.

Instructions

Check whether the LM Studio API is reachable, which URL is used, which models are loaded (with TTL) and which background tasks run. Call this first.

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": "server_status"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 11, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already declare a safe read (readOnlyHint=true, openWorldHint=false), so the bar is low; the description still adds value by disclosing the reported contents including model TTLs and task state. It does not say what the tool reports when the server is unreachable or whether it blocks/times out, which is the main remaining behavioral unknown.

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?

One compact sentence of substance plus one short imperative, with the payoff fields front-loaded and the call-first directive last. No redundant restatement of the title or annotations.

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?

With no output schema, the description carries the return-value burden and does it reasonably well by naming the four classes of information returned. It stops short of describing response shape or failure behavior, which leaves a small gap for a diagnostic 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 tool takes no parameters, so there is nothing for the description to disambiguate; baseline applies. The description's model-TTL and task-list details describe outputs rather than inputs, which is harmless but not parameter semantics.

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 and resource (check server status) and then enumerates exactly what the check surfaces: reachability, URL, loaded models with TTL, and running background tasks. An agent can distinguish this diagnostic from siblings like server_start, server_stop, or download_status without opening any schema.

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?

'Call this first' gives explicit ordering guidance that selects this tool ahead of all siblings in a typical workflow. It does not name an alternative or a when-not condition, but the sequencing rule is the relevant one for a zero-parameter health probe.

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