AI-Cognitive-Leap/agnes-the-ai-analyst
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agnes-the-ai-analyst/cli/skills/connectors.md
ZdenekSrotyr e0ce91ddb9 feat: add dataset permissions, script execution, Kamal config, CI/CD 
- SyncSettingsRepository + DatasetPermissionRepository with RBAC
- Script deploy/run/undeploy API with import sandboxing
- User sync settings API with permission checks
- 4 CLI skills (connectors, security, notifications, corporate-memory)
- Kamal production + staging configs
- GitHub Actions CI + deploy workflows
- 91 total tests passing
2026-03-27 15:40:11 +01:00

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Connectors — How to add a new data source

Existing Connectors

  • Keboola (connectors/keboola/) — Keboola Storage API
  • BigQuery (connectors/bigquery/) — Google BigQuery
  • Jira (connectors/jira/) — Jira webhook + API

Adding a New Connector

  1. Create connectors/<name>/adapter.py implementing the DataSource ABC:

    from src.data_sync import DataSource

class MyDataSource(DataSource):
    def sync_table(self, table_config, sync_state): ...
    def discover_tables(self): ...
    def get_column_metadata(self, table_id): ...
    def get_source_name(self): ...

  2. The factory in src/data_sync.py:create_data_source() auto-discovers connectors. Set DATA_SOURCE=<name> in instance.yaml or .env.

  3. Add required env vars to .env and config/.env.template.

  4. Add tests to tests/test_<name>_adapter.py.

Configuration

Each connector reads credentials from environment variables. Table definitions are in docs/data_description.md (YAML blocks).