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mujoco-mcp

mujoco_model_info

Read-onlyIdempotent

Inspect a loaded MuJoCo model's joints, actuators, sensors, bodies, and options to understand limits and layout before choosing control values or interpreting state data.

Instructions

Detailed structure of a loaded model: joint types/ranges, actuator ctrlranges, sensors, bodies, options.

Returns JSON: {session_id, source, sizes: {nq, nv, nu, na, nbody, njnt, ngeom, nsensor, nkey},
options: {timestep, gravity, integrator},
joints: [{name, type, range|null, qpos_adr, dof_adr}],
actuators: [{name, ctrlrange|null, gear}],
sensors: [{name, type, dim}], bodies: [names], keyframes: [names]}.
Use before choosing ctrl values (respect ctrlrange) or interpreting qpos/qvel layout.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the output JSON structure and usage advice, which is helpful but does not go beyond what annotations already establish. It does not contradict the annotations.

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?

The description is concise: a one-line summary followed by the JSON return structure. It is front-loaded with the purpose and the detailed structure is useful for an info tool. No waste, though the JSON block is somewhat lengthy but necessary for clarity.

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 single-parameter tool with an output schema, the description provides a complete JSON structure in text, covering all returned fields. It also gives usage context. The tool is simple and the description is sufficient for an agent to call it correctly and interpret results.

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 only parameter is session_id, which is self-explanatory from its name and type (string). Schema coverage is 0%, but the description does not elaborate on session_id, nor does it need to given its simplicity. The baseline of 3 applies because the parameter is trivial and the name is sufficient.

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 it provides detailed structure of a loaded model, listing joint types/ranges, actuator ctrlranges, sensors, bodies, and options. This verb+resource combination is specific and distinguishes it from siblings like mujoco_get_state (which deals with state values) and mujoco_step (simulation). The annotation title 'Inspect model structure' reinforces the purpose.

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 gives explicit usage context: 'Use before choosing ctrl values (respect ctrlrange) or interpreting qpos/qvel layout.' This tells the agent when to call this tool, but it does not explicitly mention alternatives or exclusions. However, the intended use case is clear, and the read-only nature is implied by the tool type.

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