`aidp-connectors-bootstrap` — first-time setup of the helper package in AIDP

aidp-connectors-bootstrap — first-time setup of the helper package in AIDP

When to use

• The user just installed the plugin and asks "how do I set this up?", "what's the first step?", "install the helpers".
• The user runs a connector skill for the first time and gets ModuleNotFoundError: No module named 'oracle_ai_data_platform_connectors'.
• The user explicitly asks to upload the helper package to AIDP.

Outcome of running this skill

• /Workspace/Shared/oracle_ai_data_platform_connectors/scripts/oracle_ai_data_platform_connectors/ exists in the user's AIDP workspace, populated from the plugin's local scripts/ directory.
• The user has run examples/00_bootstrap_helpers.ipynb once and it printed BOOTSTRAP OK.
• From that point on, every connector skill works without further setup.

What you (Claude) should do

Step 1 — locate the plugin's scripts/ directory on disk

The plugin lives wherever the user installed it. Common locations:

• ~/.claude/plugins/<marketplace>/oracle-ai-data-platform-workbench-spark-connectors/scripts/oracle_ai_data_platform_connectors/
• A local clone (when developing): the path printed by claude --plugin-dir <path>.

Run find ~/.claude/plugins -type d -name oracle_ai_data_platform_connectors 2>/dev/null (or the platform equivalent) to discover it. Confirm with the user before uploading.

Step 2 — create the destination directory in AIDP

Use the AIDP MCP tools:

mcp__aidp__create_directory(
  workspace_id="<user's workspace id>",
  path="/Workspace/Shared/oracle_ai_data_platform_connectors"
)
mcp__aidp__create_directory(
  workspace_id=...,
  path="/Workspace/Shared/oracle_ai_data_platform_connectors/scripts"
)

(If the workspace_id isn't already known from the conversation, ask the user.)

Step 3 — upload the package files

For each .py file under the local scripts/oracle_ai_data_platform_connectors/, upload to the matching path under /Workspace/Shared/oracle_ai_data_platform_connectors/scripts/. Use mcp__aidp__upload_file (or the equivalent in this MCP server).

The package layout to preserve:

oracle_ai_data_platform_connectors/
├── __init__.py
├── auth/{__init__,wallet,dbtoken,oci_config,user_principal,secrets}.py
├── jdbc/{__init__,oracle,hive}.py
├── rest/{__init__,fusion,epm,essbase}.py
└── streaming/{__init__,kafka}.py

Step 4 — push the bootstrap notebook to AIDP and run it

Upload examples/00_bootstrap_helpers.ipynb to Shared/connectors-tests/00_bootstrap_helpers.ipynb via mcp__aidp__nb_save_file. Then mcp__aidp__nb_create_session against the user's chosen cluster (typically tpcds), and mcp__aidp__nb_execute_code for each cell. The final cell prints BOOTSTRAP OK if everything works.

Step 5 — confirm

Tell the user:

• Where the helpers landed.
• That every connector skill in this plugin will now work.
• The next step is to pick a connector (e.g., aidp-atp) and supply that connector's env vars / Vault secrets.

Alternative: ask the user to install via PyPI (v1.0+)

Once the package is published to PyPI, this skill should pivot to telling the user to run %pip install oracle-ai-data-platform-connectors in any AIDP cell instead of uploading. Until v1.0 ships, the Workspace-upload path above is the only way.

What NOT to do

• Do not upload anything to /Workspace/Shared/ without confirming the path with the user (in case they have an existing convention).
• Do not write secrets, .env contents, or PEM keys anywhere in /Workspace/Shared/. The helper package is code-only.
• Do not skip the sanity-import notebook — it's how you (and the user) confirm the upload worked, not just that files exist.

References

• Bootstrap notebook: examples/00_bootstrap_helpers.ipynb
• Plugin README install section: README.md