Use this checklist before making the enhanced MCP repository public or linking it from bpy.dev.
- Add repository license file:
LICENSE. - Add attribution/provenance notice:
NOTICE.md. - Confirm upstream SPDX license markers: GPL-3.0-or-later.
- Decide final public name/package namespace (
bpy-dev-mcp,bpydev-mcp, or another name). - Decide whether this repo remains a fork or is imported into a clean public repo.
- Ignore local Hermes planning/session files via
/.hermes/. - Ignore common build/cache artifacts.
- Confirm no generated trial media or temporary outputs are tracked.
- Confirm no obvious credentials, tokens, private keys, or private paths are tracked by the publication-prep scan. Remaining API-key references are environment-variable examples/tests, not literal secrets.
- Confirm tracked file sizes are ordinary source/docs/fixture sizes; largest tracked files are bundled API docs and small deterministic
.blendfixtures.
- Add security model:
SECURITY.md. - Add developer-preview overview to
readme.md. - Add backend documentation:
readme_bpy_backend.rst. - Document benchmark limitations in
benchmarks/token_efficiency/README.md. - Add final package install commands after package naming is decided.
- Add public
bpy.devlink after the website repo is live.
- Install/help smoke via
uv run --directory mcp blender-mcp --help. - Run saved-file/runtime validator smoke with Blender executable backend.
- Run saved-file/runtime validator smoke with standalone
bpybackend. - Run runtime API docs smoke through the unit/integration suite.
- Run deterministic benchmark validator tests.
- Run tracked-file secret scan.
- Run
git diff --check.
- Copy Trial 017 videos into the website repo or CDN/object storage.
- Publish Trial 017 only as an exploratory case study.
- Keep deterministic benchmark results separate from creative/VLM demo results.
- Do not claim definitive superiority from a single creative trial.
Developer preview focus:
- saved-file/headless Blender MCP execution;
- standalone
bpybackend option; - runtime Blender Python API lookup;
- subprocess/capture/transport hardening;
- deterministic benchmark tasks and telemetry scaffolding;
- exploratory creative comparison tooling.