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OMERO Integration

Free

Automate and inspect microscopy data workflows securely.

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Free · Opens the source repo

What OMERO Integration does

The OMERO Integration skill enables users to efficiently manage and automate workflows involving microscopy data stored on OMERO servers. With a focus on secure operations, this skill leverages the capabilities of the OMERO Python client (omero-py), BlitzGateway, and OMERO CLI to facilitate interactions with microscopy data. Users can perform tasks such as querying images, managing annotations, and exporting metadata while ensuring compliance with data security protocols.

This skill is particularly useful for researchers and developers who work with large datasets in microscopy. It provides a structured approach to accessing and manipulating data, allowing for scoped inventory management, metadata export, and import/export planning. The integration with OMERO's documented APIs ensures that users can effectively utilize the available resources without compromising data integrity or security.

The skill also includes several bundled scripts that assist with configuration validation, inventory listing, and metadata exportation. These scripts operate in a dry-run mode by default, which means users can validate their commands without affecting the live data. This feature is crucial for maintaining data security and preventing accidental modifications. Additionally, the skill emphasizes the importance of proper connection management and credential handling, ensuring that sensitive information is not exposed during operations.

Overall, the OMERO Integration skill is designed for users who require a reliable and secure method to interact with microscopy data, making it a valuable addition to any data management toolkit in scientific research.

When to use it

Use this skill when you need to interact with microscopy data in OMERO, especially for tasks requiring secure access and automation.

When not to use it

This skill may not be suitable for users who do not require the specific capabilities of OMERO or those looking for a more general data management tool.

What you can build with it

Automating Metadata Exports

Use the skill to automate the export of image metadata from OMERO, ensuring that sensitive data is handled securely.

Validating Configuration Settings

Before connecting to an OMERO server, utilize the validation script to ensure that all configuration settings are correct.

Creating Scoped Inventory Reports

Generate read-only object inventories from OMERO to maintain an overview of available microscopy data without risking data integrity.

How to install OMERO Integration

View source

1. Install with the skills CLI

npx skills add k-dense-ai/scientific-agent-skills/omero-integration --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by k-dense-ai

OMERO Integration

Use current OME documentation and the smallest explicit data scope. OMERO data may contain unpublished images, identifiers, annotations, original files, and derived measurements.

Verified Baseline

This skill was refreshed on 2026-07-23:

  • OMERO.server 5.6.18 (May 2026) is the current documented stable server.
  • It was tested by OME with OMERO.py/omero-py 5.22.1 and OMERO.web 5.31.0.
  • omero-py==5.22.1 requires Python 3.10 or newer. The OMERO support matrix supports 3.10 and 3.11, recommends 3.12, and still labels 3.13/3.14 “upcoming.”
  • OMERO 5.6 uses IcePy 3.6, with 3.6.5 prebuilt client wheels documented for Python versions through 3.12.

The pin above is a reproducible skill snapshot, not a promise that every OMERO.server release accepts that client. For another server version, consult its release entry and use the OMERO.py version tested with it. See references/sources.md.

Operating Contract

  1. Start with local validation or a dry run. Do not connect until the user has selected the host, group, object type, IDs, and result limit.
  2. Read credentials only from the named OMERO_* variables in the frontmatter. Never search parent directories or load .env files.
  3. Never place a password or session key in command arguments, source code, output JSON, logs, tracebacks, or chat. A session key is a bearer credential.
  4. Default to secure=True. OMERO encrypts login by default, but post-login data and the session ID may otherwise travel unencrypted. secure=True does not by itself guarantee certificate hostname verification.
  5. Bound every list, page, ROI, shape, annotation, table row, pixel plane, and local file scan. Do not turn an object request into a group-wide or cross-group export without explicit approval.
  6. Treat all writes separately: annotation/link creation, rendering-default saves, image creation, imports, script uploads, table writes, ownership or group changes, and deletion require an exact reviewed target.
  7. Close BlitzGateway, table handles, raw stores, thumbnail stores, rendering engines, script clients, and other stateful services in finally blocks or documented context-manager patterns.
  8. Never connect to a real server merely to “test” examples.

Choose the Interface

  • BlitzGateway (omero-py): primary Python client for object traversal, pixels, annotations, ROIs, rendering, and services.
  • OMERO CLI: sessions, import scanning/import, OME-TIFF or XML export, scripts, and administrative plugins. Most client commands are remote; import also needs the matching server-side Java libraries through OMERODIR.
  • OMERO.web api and webgateway: the only OMERO.web apps that official documentation calls stable public APIs. The documented JSON API is version-discovered and has limited object coverage; it is not evidence that every webclient URL is a supported REST endpoint.
  • OMERO.server scripts: uploaded plugins executed by server infrastructure. They are different from the bundled local client helpers in scripts/.

Install a Reproducible Client

Create a Python 3.12 environment:

uv venv --python 3.12 .venv
source .venv/bin/activate

Install the exact IcePy 3.6.5 wheel matching the interpreter, OS, architecture, and wheel tags, then OMERO.py:

# Download the matching 3.6.5 wheel from the official OMERO-linked matrix.
uv pip install "/absolute/path/to/zeroc_ice-3.6.5-<matching-tags>.whl"
uv pip install "omero-py==5.22.1"

Do not substitute Ice 3.7: the OMERO 5.6 support matrix marks Ice 3.6 as recommended and 3.7 as unsupported. A plain install may attempt to compile IcePy from source; prefer a reviewed matching wheel. The upstream package is GPL-2.0-or-later; this skill’s own files are MIT.

For import/admin commands only, OMERODIR must point to a compatible extracted OMERO.server directory. A normal remote BlitzGateway client does not require that server tree. Read references/connection.md before installation or authentication work.

Credentials and Connection

Set named variables in the calling environment or secret manager. Do not put the password on an omero CLI command:

export OMERO_HOST="omero.example.org"
export OMERO_PORT="4064"
export OMERO_USER="researcher"
export OMERO_SECURE="true"
# Supply OMERO_PASSWORD through the environment/secret manager, or use
# OMERO_SESSION_KEY as an alternative. Do not echo either value.

A password-authenticated, exception-safe read pattern is:

import os
from omero.gateway import BlitzGateway

conn = None
try:
    conn = BlitzGateway(
        os.environ["OMERO_USER"],
        os.environ["OMERO_PASSWORD"],
        host=os.environ["OMERO_HOST"],
        port=int(os.environ.get("OMERO_PORT", "4064")),
        secure=True,
    )
    if not conn.connect():
        raise RuntimeError("OMERO connection failed")

    images = conn.getObjects(
        "Image",
        opts={"limit": 25, "offset": 0, "order_by": "obj.id"},
    )
    for image in images:
        print(image.getId())  # Do not print names unless requested.
finally:
    if conn is not None:
        conn.close()

For existing-session and CLI prompt patterns, certificate verification, group context, and cleanup details, read references/connection.md.

Bundled Safe Helpers

All helpers use argparse; --help works without OMERO installed. Remote helpers are dry-run by default and require --execute.

python -B scripts/validate_config.py --help
python -B scripts/inventory.py --help
python -B scripts/export_image_metadata.py --help
python -B scripts/plan_transfer.py --help
  • validate_config.py: validates only named endpoint/auth variables locally; optional DNS resolution still does not contact OMERO.
  • inventory.py: bounded, read-only object inventory with paged JSON output.
  • export_image_metadata.py: explicit-image annotation/ROI JSON export with redaction defaults and per-category limits; it never downloads file bytes or pixels.
  • plan_transfer.py: local-only import scan or per-image export plan; it never invokes OMERO and never emits credential flags.

Read references/scripts.md before using them.

Capability Guide

Final Review Before Remote Work

  • Confirm server version and its tested OMERO.py pairing.
  • Confirm target host, SSL router port, user/session, and one group.
  • Confirm exact object IDs/types and hard limits.
  • Confirm whether names, annotation values, file names, ROI labels, owner names, pixels, or original files may leave the server.
  • Show the proposed output path and refuse overwrite unless explicitly allowed.
  • For a write, show the mutation and target IDs separately from any read plan.
  • Close every connection/service even after partial failure.

Frequently asked questions about OMERO Integration

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