Harbor AIops
Governed Harbor container-registry operations with 39 MCP tools and corresponding CLI commands. Every call is audited and budgeted by the bundled governance harness. Artifact scan, tag creation and high-risk tag deletion have dry-run previews; uncertain results are reported as outcomeUnknown.
What it checks
- Component health and system volume use.
- Projects, repository inventory, artifacts, tags, vulnerability reports, quotas and project audit logs.
- Registry statistics, project members, tag immutability rules, labels and robot metadata (secrets redacted).
- Latest registry-wide and scheduled scan metrics, plus bounded artifact scan report logs.
- Guarded deletion of one proven, mutable tag with an absence post-check.
- Garbage collection execution history.
- GC execution details and bounded plain-text logs.
- Replication policies, executions, tasks and bounded task logs.
- Retention policy, execution, tasks and bounded task logs by actual IDs.
harbor_diagnosecombines health, volume, GC and replication observations. Failed probes appear as errors withdata: null.
Lists have items, returned, limit, and measured truncated fields. They are capped at 500 records per call.
Setup from source
Requires Python 3.11+, uv, and a Harbor instance. Install locally with uv sync --dev. Run uv run harbor-aiops init to configure an HTTPS target and encrypt its password, or create ~/.harbor-aiops/config.yaml with a targets list:
targets:
- name: primary
host: harbor.example.com
username: robot$ops
scheme: https
port: 443
verify_ssl: true
timeout: 30
Run uv run harbor-aiops secret set primary, then uv run harbor-aiops doctor and uv run harbor-aiops diagnose. The MCP entry point is uv run harbor-aiops-mcp. Set HARBOR_AIOPS_MASTER_PASSWORD for noninteractive secret-store access. TLS verification is enabled by default; ca_file accepts a custom CA PEM.
Scope and verification
The scan-artifact command starts an asynchronous scan and reports an unknown final outcome until its status is checked. create-tag proves the tag was absent and checks that it appeared after the write. delete-tag requires an exact mutable tag on the specified digest, previews the target and confirms absence after deletion. Neither tag write mints an undo token because immutability and later artifact changes can make the inverse unsafe. Retention execution, replication restart, GC start/stop, artifact deletion and policy changes remain outside this release until their actual outcomes and recovery paths can be verified on disposable Harbor. See verification. Missing operations and live-environment feedback are welcome as issues or PRs.
Development
uv run pytest -q, uv run ruff check ., and uv run bandit -r harbor_aiops -ll are local checks. Root handbook gates must pass before release.
Metadata
Release files for harbor-aiops 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| harbor_aiops-0.2.0.tar.gz | 80.1 kB | With provenance | Details for harbor_aiops-0.2.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| harbor_aiops-0.2.0-py3-none-any.whl | Python 3 | none | any | Details for harbor_aiops-0.2.0-py3-none-any.whl |
Total release size: 146.1 kB
Release files / harbor_aiops-0.2.0.tar.gz
| Download URL | harbor_aiops-0.2.0.tar.gz |
|---|---|
| Size | 80.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / harbor_aiops-0.2.0-py3-none-any.whl
| Download URL | harbor_aiops-0.2.0-py3-none-any.whl |
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| Size | 65.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
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twine/7.0.0 CPython/3.13.16
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Provenance
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PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Nov 5, 2026.
Transparency logSecurity for harbor-aiops 0.2.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
Full provenance
All 2 files in this release have been uploaded with provenance metadata.
Attestation for harbor_aiops-0.2.0.tar.gz
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Nov 5, 2026.
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