pixlint

PixLint

Lint, curate, and prepare computer-vision datasets — right from your AI assistant.

PixLint is an MCP server that gives AI assistants — Claude, Cursor, VS Code, and any MCP client — direct, conversational access to a complete computer-vision dataset toolkit: analyze quality, find duplicates and label errors, clean and curate, split, augment, convert formats, and export to every major training framework.

It runs locally over stdio, or self-hosted on the internet over authenticated HTTP.

Why PixLint

Most dataset tooling is either a paid SaaS or a heavy GUI app. PixLint is a single, open-source, self-hostable server an AI agent can drive end to end — and it does things others keep behind paid tiers:

• 🩺 Dataset Doctor — one call runs a full diagnostic and returns a prioritized, executable fix plan.
• Label-error detection — automatically surface images that are probably mislabeled.
• Natural-language query — "find blurry images with a person on the left", answered over your data.
• Weak-slice discovery — find under-represented or low-quality slices to collect or augment next.
• Curation that writes a new dataset — clean / filter / remap, not just report.
• Auto-labeling with a pretrained detector, and one-command Hugging Face publishing.

Features

103 operations — 67 tools, 23 resources, 13 prompts.

Category	What you get
Load	COCO · VOC · YOLO · KITTI · folder, plus cloud (S3 / GCS / Azure)
Analyze	Duplicates · quality (blur/exposure/noise/contrast) · integrity · class distribution · embeddings · semantic search · outliers · health score
Data intelligence	Dataset Doctor readiness report · label-error detection · natural-language query · weak-slice / bias discovery
Curate	Filter to a subset · clean (corrupt / out-of-bounds / degenerate / duplicates) · remap classes — each produces a new dataset
Augment & transform	YOLO/classification/segmentation pipelines · resize · normalize · format conversion
Split	Stratified / random / temporal / grouped · k-fold · data-leakage detection
Auto-label	Pretrained COCO-80 detector → pre-annotated dataset
Export & publish	PyTorch · TensorFlow · Ultralytics · HDF5 · WebDataset · FiftyOne · CVAT · LabelMe · Hugging Face Hub
Pipelines	Compose multi-step workflows and reuse pre-built templates

Quick Start

1. Install

pip install pixlint

Optional extras add heavier capabilities:

pip install "pixlint[torch]"        # embeddings, auto-labeling, label-error detection
pip install "pixlint[huggingface]"  # Hugging Face export + publishing
pip install "pixlint[all]"          # everything

2. Connect your AI assistant

Claude Desktop — claude_desktop_config.json:

{
  "mcpServers": {
    "pixlint": {
      "command": "pixlint",
      "env": { "CV_DATA_DIR": "/path/to/your/datasets" }
    }
  }
}

Cursor / VS Code — .cursor/mcp.json or .vscode/mcp.json:

{
  "mcpServers": {
    "pixlint": {
      "command": "pixlint",
      "env": { "CV_DATA_DIR": "/path/to/your/datasets" }
    }
  }
}

CV_DATA_DIR is the directory PixLint is allowed to read datasets from.

3. Just ask

"Load my dataset at /data/coco_person, give it a readiness report, then clean it and export for YOLO."

Your assistant calls the right PixLint tools in sequence — diagnose, clean, split, export — and hands back a training-ready dataset.

Security

PixLint touches the filesystem and can be exposed to a network, so protections run on every tool call:

• Paths are confined to your configured data directory (reads and writes).
• Credentials come only from environment variables, never tool inputs.
• Per-call rate limiting, concurrency limits, and audit logging.
• Decompression-bomb protection on image decode.
• Optional bearer-token authentication for the HTTP transport.

See the Security Guide for the full threat model and the recommended production checklist.

Documentation

Guide	Description
Getting Started	Installation, configuration, first steps
MCP Client Setup	Claude, Cursor, VS Code, and remote/HTTP hosting
API Reference	All 67 tools with parameters
Security Guide	Threat model, configuration, hosting
Pipeline Templates	Pre-built and custom pipelines

Runnable scripts live in examples/. See CHANGELOG.md for release notes.

License

PixLint is source-available under the PolyForm Strict License 1.0.0 — see LICENSE. You may use it for permitted (noncommercial) purposes; commercial use, redistribution, or modification requires a separate license from the copyright holder. Contributions are welcome via pull request.

_{mcp-name: io.github.amitsingh-24/pixlint}