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amanharshx

ultralytics-mcp

by amanharshx
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TypeScript
Remote

model_predict

Read-only

Run inference on an image supplied as a URL or base64 data using a trained Ultralytics model. Adjust confidence, IoU, and image size thresholds to control prediction accuracy.

Instructions

Run inference with a trained model on an image URL or base64 source (no local file paths).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
iouNoIoU threshold used for NMS (0-0.95, server default applies if omitted).
confNoConfidence threshold (0.01-1, server default applies if omitted).
imgszNoInference image size (32-1280, server default applies if omitted).
modelYesModel ref by owner/project/model, ul:// URI, or slug (requires project).
sourceYesImage URL, raw base64-encoded image, or base64 data: URI (data:<mime>;base64,<payload>). Local file paths are not supported.
projectNoProject ref required when model is given by slug.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv0.1.13
    • addedInput schema / properties / conf / description
      Added value: +"Confidence threshold (0.01-1, server default applies if omitted)."
    • addedInput schema / properties / imgsz / description
      Added value: +"Inference image size (32-1280, server default applies if omitted)."
    • addedInput schema / properties / iou / description
      Added value: +"IoU threshold used for NMS (0-0.95, server default applies if omitted)."
  2. Changed3 schema fields changedv0.1.12
    • changedInput schema / properties / model / description
      Previous value: -"Model id, or slug when project is also provided."New value: +"Model ref by owner/project/model, ul:// URI, or slug (requires project)."
    • addedInput schema / properties / project / description
      Added value: +"Project ref required when model is given by slug."
    • changedInput schema / properties / source / description
      Previous value: -"Image URL or base64 input string. Local file paths are not supported."New value: +"Image URL, raw base64-encoded image, or base64 data: URI (data:<mime>;base64,<payload>). Local file paths are not supported."
  3. Changed2 schema fields changedv0.1.6
    • addedInput schema / properties / model / description
      Added value: +"Model id, or slug when project is also provided."
    • addedInput schema / properties / source / description
      Added value: +"Image URL or base64 input string. Local file paths are not supported."
  4. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds context that inference is performed on URL/base64 sources and explicitly excludes local file paths, but it does not describe output behavior, errors, or other runtime expectations. This is adequate but not rich.

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?

A single sentence that states the action, resource, accepted source formats, and key exclusion with no filler. The most important information is front-loaded and everything included adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description handles the core purpose and source input well, and the schema covers parameter details. However, with no output schema, no mention of the return payload or errors, and no differentiation from deployment_predict, the definition is functional but not fully complete for an agent deciding how to invoke it.

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 input schema has 100% parameter description coverage, documenting model, source, project, conf, iou, and imgsz. The description only restates the source constraints and model context already present in the schema, adding no new parameter-level meaning, so the baseline score of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the operation ('Run inference') and resource ('with a trained model'), plus the accepted image source forms (URL or base64). It is specific and immediately understandable, though it does not explicitly distinguish itself from the sibling deployment_predict tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus deployment_predict or other inference-related siblings. The only directional constraint is 'no local file paths', which is more about the source parameter than about tool selection, so an agent is left to infer the appropriate context.

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

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