Skip to main content
Glama
amanharshx

ultralytics-mcp

by amanharshx
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

models_list

Read-only

List models within a project by slug, owner/slug, or ul:// URI; for model quality, use model_metrics.

Instructions

List models in a project by slug, owner/slug, or project ul:// URI. Model quality is not included; use model_metrics, which validates the platform's best-epoch fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum models to return. Omit for the server default (currently 20); the API currently accepts up to 100.
projectYesProject ref by slug, owner/slug, or ul:// URI.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.1.15
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / limit
      Added value: +{
+  "description": "Maximum models to return. Omit for the server default (currently 20); the API currently accepts up to 100.",
+  "type": "number"
+}
  2. Changed1 schema field changedv0.1.12
    • changedInput schema / properties / project / description
      Previous value: -"Project ref by id, slug, username/slug, or ul:// URI."New value: +"Project ref by slug, owner/slug, or ul:// URI."
  3. Changed1 schema field changedv0.1.6
    • addedInput schema / properties / project / description
      Added value: +"Project ref by id, slug, username/slug, or ul:// URI."
  4. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds genuine scope disclosure by stating what the return does NOT contain (model quality), which is real behavioral context beyond the annotations, though it says nothing about pagination or result ordering.

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?

Two tightly packed sentences with zero waste; the core purpose and identifier forms lead, and the exclusion/alternative note follows. Every clause earns its place.

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?

No output schema exists, and the description partially compensates by stating what the result omits and where to get that data instead. Neither pagination behavior nor return shape is explained, but for a simple read-only list tool with fully-covered parameters, the coverage is nearly sufficient.

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?

Schema description coverage is 100%, so both parameters (project and limit, including the default-20/up-to-100 nuance) are fully documented in the schema. The description restates the accepted project identifier formats but adds no meaning beyond the schema, so the baseline 3 applies.

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 ("List models in a project") plus the accepted identifier forms, and distinguishes itself from siblings by explicitly noting that model quality is excluded. An agent can tell this apart from models_get, model_metrics, and model_plots 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?

Names the alternative (model_metrics) and the condition that selects it (when you need quality / best-epoch validation). It does not explicitly contrast against models_get for single-model retrieval, so routing is clear but not complete.

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

Deploy Server

Other Tools