Skip to main content
Glama

list_instances

List all running app windows (instances) with their id, display, name, command, and status, including sandboxes started outside the server. Use to discover available instances and verify one is active before driving it.

Instructions

List all instances (running app windows): id, display, name, command, up.

Returns {"ok", "count", "instances": [{instance, display, name, command, up}, …]}. Probes displays :1–:12 for sandboxes started outside this server (e.g. start-display.sh), so it also finds instances this process didn't launch (their name/command show as unknown). Use it to discover what you can drive and to verify an instance is up before acting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations provided, the description fully covers behavioral traits: it reveals that the tool probes displays :1–:12 to find sandboxes started externally, notes that instances not launched by this process show 'unknown' name/command, and describes the exact JSON return structure.

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 with two clear paragraphs: first defines the tool and its output, second explains an important behavioral nuance. Every sentence adds value without redundancy.

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?

Given the tool has no parameters and an output schema exists, the description still explains the return format and key behavioral details (external instance detection). This is complete and sufficient for an agent to use the tool correctly.

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 has zero parameters, so per guidelines the baseline is 4. Since there are no parameters to describe, the description appropriately adds no parameter information.

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 tool lists all running app windows (instances) and specifies the returned fields (id, display, name, command, up). It is a unique resource distinct from sibling tools like click or launch_app, making its purpose unmistakable.

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 provides explicit usage context: 'Use it to discover what you can drive and to verify an instance is up before acting.' However, it does not explicitly mention when not to use it or contrast with alternatives, so it lacks exclusions.

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

Install Server

Other Tools

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/segentic-lab/glovebox-mcp'

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