albumentationsx-mcp 0.2.0

Model Context Protocol server for AlbumentationsX augmentation discovery, validation, and previews.

AlbumentationsX MCP

Model Context Protocol server for AlbumentationsX: discovering transforms, validating augmentation pipelines, rendering deterministic previews, and exporting reproducible pipeline specs.

Scope

This project is intentionally a thin MCP layer around existing AlbumentationsX primitives:

• albu-spec is the source of transform metadata, parameter constraints, targets, and docstrings.
• albumentationsx remains the execution engine for validation, serialization, and previews.
• the MCP server exposes resources, tools, and prompts with strict typed schemas and bounded local file access.

The server does not execute arbitrary Python, fetch remote images, overwrite datasets, or train models.

Install

Run the published MCP server without cloning:

uvx --from albumentationsx-mcp albumentationsx-mcp

For local development:

uv sync --all-extras --dev

Run

uv run albumentationsx-mcp

Claude Desktop or another JSON-configured MCP host can launch a local checkout with stdio:

{
  "mcpServers": {
    "albumentationsx": {
      "command": "uv",
      "args": ["run", "albumentationsx-mcp"],
      "cwd": "/path/to/albu-mcp"
    }
  }
}

Installed from PyPI:

{
  "mcpServers": {
    "albumentationsx": {
      "command": "uvx",
      "args": ["--from", "albumentationsx-mcp", "albumentationsx-mcp"]
    }
  }
}

See examples/claude_desktop_pypi_config.json, examples/cursor_mcp_config.json, and examples/codex_mcp_config.toml for copyable host snippets.

Core Tools

• search_transforms: search transform metadata by query, targets, type, and bbox support.
• get_transform_schema: inspect a transform schema and constraints.
• validate_pipeline: validate a typed pipeline spec before running it.
• recommend_pipeline: create a conservative task preset for classification, detection, segmentation, or OCR.
• adjust_pipeline: apply structured preview feedback such as too_noisy or too_blurry.
• explain_pipeline: summarize likely effects, preview risks, and useful feedback tags.
• list_feedback_tags: list the structured feedback contract used by adjust_pipeline.
• render_preview: create deterministic local preview artifacts inside an allowed output root.
• render_preview_batch: create deterministic multi-image preview contact sheets using the same request schema.
• compare_preview_runs: compare two preview manifests before choosing feedback tags or exporting a pipeline.
• list_preview_runs: list recent preview manifests recorded under the artifact root.
• get_preview_manifest: read one recorded preview manifest by run id.
• delete_preview_run: delete one preview run and its artifacts.
• cleanup_preview_runs: prune older preview runs beyond a retention count.
• export_pipeline: export a pipeline as Python, JSON, or YAML.

render_preview and render_preview_batch support optional bboxes, keypoints, and mask paths for annotation overlay previews. Preview manifests include an agent-legible summary block with input counts, seeds, transform names, artifact counts, contact sheets, and warnings.

See docs/USAGE.md for an end-to-end MCP host workflow, docs/RELEASE.md for the package and MCP Registry release process, server.json for public discovery metadata, and evals/golden_mcp_scenarios.yaml for executable MCP scenarios.

Verification

uv run pytest
uv run ruff check .
uv run ruff format --check .
uv run ty check
uv run python scripts/run_golden_evals.py
uv build