Skip to main content
Glama
whats2000

Isaac Sim MCP Server

get_isaac_logs

Retrieve recent WARN/ERROR logs and captured print output from the current Isaac Sim run to diagnose issues without clearing the buffer.

Instructions

Diagnostic tool: recent WARN/ERROR logs plus captured print() output.

Captures carb.log_*/omni.log WARN+ERROR and stdout from execute_script / reload_script (tagged [PRINT]). Plain print() outside those captured contexts may not appear.

Defaults are agent-friendly: non-destructive (clear=False) and scoped to the current run (since_last_play=True) so you see logs from what you just did, not stale entries from previous runs.

Args: clear: If True, empty the buffer after reading. Default False. count: Maximum number of log entries to return. since_last_play: If True (default), return only entries since the last timeline Play. Set False for the full buffer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
clearNo
countNo
since_last_playNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.6.1
    • changedInput schema / properties / clear / default
      Previous value: -trueNew value: +false
    • addedInput schema / properties / since_last_play
      Added value: +{
      +  "default": true,
      +  "title": "Since Last Play",
      +  "type": "boolean"
      +}
  2. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and does so thoroughly. It discloses what is captured, what may not appear, the non-destructive default, the scoping behavior, and the side effect of clear=True. This gives the agent an accurate behavioral model beyond the raw schema.

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 well-organized and front-loaded with the core purpose. The capture scope, limitation, defaults, and parameter explanations each earn their place with no filler. The Args section is concise and directly actionable.

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?

The tool is simple, has no required parameters, and includes an output schema, so the description does not need to explain return values. It covers operational context, behavioral caveats, and all parameter semantics. Nothing essential is missing for correct invocation.

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

Parameters5/5

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

Input schema has 0% description coverage, so the description must explain the parameters, and it does. Each parameter is documented with its effect, default, and how it changes behavior. This fully compensates for the schema gap.

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 opens with a clear statement that this is a diagnostic tool for recent WARN/ERROR logs plus captured print() output. It names the specific log sources (carb.log_*/omni.log) and distinguishes captured stdout contexts. This is unambiguous and sufficiently distinct from all sibling tools.

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 clear usage context: it is for viewing logs from execute_script / reload_script and current-run activity, with agent-friendly defaults. It explains how to see the full buffer via since_last_play=False and that clear=True is destructive. It does not explicitly name alternatives, but no sibling tool overlaps with log retrieval.

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