Operate the entire Oracle AI Data Platform (AIDP) Workbench in natural language — a 37-skill agent (not a single-engine orchestrator). Discovers your catalog into a grounding cache (FK/join hints + value dictionaries), turns plain English into accurate Spark SQL, and runs the full lakehouse SQL lifecycle (CREATE/INSERT/UPDATE/DELETE/MERGE/OPTIMIZE/VACUUM/DESCRIBE HISTORY/time-travel on the Spark/Delta lakehouse). Ingests files, profiles data and sets quality rules, authors and repairs cron pipelines, provisions clusters (Compute/AI Compute), and debugs via the Spark UI. Governs the platform (roles + per-resource permissions, credential store, Delta Sharing, audit logs, user settings; plus native Git, bundles, and MLOps/MLflow in Preview) and ships AI — Agent Flows across 13 node types with guardrails (content moderation, prompt-attack prevention, PII detection), Knowledge Base RAG, high-code LangGraph/aidputils agents, and reusable Tools. A semantic model + verified-query repository are matched before free generation for accuracy. Signature differentiators: LLM-in-SQL via ai_generate('openai.gpt-5.4', '<prompt>') and cross-source federation in one Spark session. Runs via the official Oracle aidp CLI with an oci raw-request REST fallback — under either api_key or oci-session-token auth. Additive to your Oracle stack.
Discover, author, deploy, and run AIDP agent flows. Use when the user wants to list/inspect agent flows, or create/update/deploy/run a flow, manage sessions/guardrails, attach compute, or attach a remote MCP server to a flow (an MCP_TOOL node — AIDP's "Native MCP Client Support" LA feature, where the flow connects OUT to OAC/ADW/OIC/any MCP-compatible service). Everything runs over the Limited-Availability AgentFlows REST API via `oci raw-request`; verify live first. (An `aidp` MCP `list_agent_flows`, if configured, is an optional read accelerator only.)
Build AIDP agents in high-code Python with aidputils + LangGraph (the code-first alternative to the low-code agent-flow canvas). Use when the user wants to write an agent in Python, use LangGraph / create_react_agent / StateGraph, call aidputils (OCIAIConf, AIDPToolConf, init_oci_llm, create_langgraph_tool), build a custom or multi-agent supervisor flow in code, or asks "how do I code an AIDP agent". For the low-code/REST node-graph path use aidp-agent-flows.
Run LLM functions inside Spark SQL on AIDP via ai_generate(). Use when the user wants to summarize/classify/extract/enrich rows with an LLM directly in SQL, generate narratives over aggregated results, or do grounded RAG-style analysis in the lakehouse. Signature is model-first; available models must be confirmed live before relying on it.
Answer business questions over the AIDP lakehouse with Spark SQL. Use when the user asks a data question ("how many…", "top N…", "show me…", "trend of…", "revenue by…") or wants to run ad-hoc Spark SQL. Grounds in .aidp/catalog.md + .aidp/semantic.md and reuses validated verified queries before generating SQL, then executes via the bundled aidp_sql.py helper.
Manage and search AIDP audit logs — enable/disable auditing, set retention, and query audit-log entries for a DataLake. Use when the user asks about audit logging, who did what, compliance/retention of AIDP activity, or wants to search audit events. Self-contained — official `aidp audit` CLI preferred, `oci raw-request` fallback.
This repository is a personal development marketplace for Claude Code plugins authored by Ahmed Awan.
The directory layout mirrors the canonical Oracle home at oracle-samples/oracle-aidp-samples/ai/claude-code-plugins/ so plugins move between the two repos as a flat copy.
| Plugin | What it does | Canonical home |
|---|---|---|
oracle-ai-data-platform-workbench-engineer-agent | Natural-language agent that operates the entire AIDP Workbench — catalog discovery, Spark-SQL + full Delta DDL/DML, ingestion, profiling/quality, pipelines, clusters, Spark-UI debugging, governance (roles/credentials/Delta Sharing/MLOps/audit), and AI (Agent Flows + guardrails, Knowledge Base RAG, high-code LangGraph agents). Signature: LLM-in-SQL via ai_generate() + cross-source federation. 37 skills; api_key or session-token auth. | pending PR to oracle-samples |
oracle-ai-data-platform-workbench-spark-connectors | 18 model-invokable skills connecting Oracle AI Data Platform Workbench Spark notebooks to Oracle (ALH/ADW/ATP, ExaCS, Fusion ERP, BICC, EPM Cloud, Essbase) and external (PostgreSQL, MySQL/HeatWave, SQL Server, Snowflake, Azure ADLS Gen2, AWS S3, OCI Streaming, Object Storage, Iceberg, generic REST/JDBC, Excel) data sources. | oracle-samples/oracle-aidp-samples/ai/claude-code-plugins/oracle-ai-data-platform-workbench-spark-connectors/ |
oracle-ai-data-platform-fusion-bundle (alpha — pre-release) | Productized Fusion → AIDP pipeline. Curated BICC extracts, bronze/silver/gold medallion in Delta, conformed COA/calendar/org/supplier/item dimensions, AR/AP/GL/PO/Supplier-Spend gold marts, and OAC workbooks installed via OAC REST API (Authorization Code + PKCE). Live-validated end-to-end against saasfademo1 Fusion demo pod + an OAC instance. 118 unit tests passing. | pending PR to oracle-samples |
End users should install from Anthropic's community marketplace (sources from the canonical Oracle home):
/plugin marketplace add anthropics/claude-plugins-community
/plugin install <plugin-name>
This personal mirror is intended for pre-release / development snapshots — to install from here directly:
/plugin marketplace add ahmedawan-oracle/claude-code-plugins
/plugin install <plugin-name>@aidp-connectors
.
├── .claude-plugin/
│ └── marketplace.json ← marketplace definition; one entry per plugin
├── claude-code-plugins/
│ └── <plugin-name>/ ← plugin root (one per plugin)
│ ├── .claude-plugin/
│ │ └── plugin.json
│ ├── README.md
│ ├── CHANGELOG.md
│ ├── LICENSE
│ ├── skills/
│ ├── scripts/ (optional — Python helpers)
│ ├── examples/ (optional — runnable notebooks)
│ └── tests/ (optional — unit tests)
├── README.md ← this file
└── LICENSE ← repo-wide MIT
The marketplace.json at the root references each plugin via a relative source field pointing at its subdirectory under claude-code-plugins/.
mkdir -p claude-code-plugins/<plugin-name>/.claude-plugin/.claude-plugin/marketplace.json with "source": "./claude-code-plugins/<plugin-name>/".claude plugin validate . (in the repo root).oracle-samples/oracle-aidp-samples/ai/claude-code-plugins/<plugin-name>/ via PR for the canonical / community-marketplace home.Repo-wide MIT. Each plugin also ships its own LICENSE.
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Oracle AI Data Platform Workbench Spark connectors for Claude Code. 23 connector skills covering every data source workbench customers commonly need: Oracle Autonomous DB family (ALH/ADW/ATP) via wallet/IAM-DB-Token/API-key, generic Oracle Database, ExaCS, Oracle PeopleSoft, Oracle Siebel, Fusion ERP REST, Fusion BICC, EPM Cloud Planning, Essbase 21c, OCI Streaming (Kafka), OCI Object Storage, Apache Iceberg, plus PostgreSQL, MySQL/HeatWave, SQL Server, Apache Hive, Salesforce, Snowflake, Azure ADLS Gen2, AWS S3, generic REST, custom JDBC, and Excel. v0.5.0 adds 5 new connectors plus pushdown.sql / catalog.id / manifest.path patterns from oracle-samples PR #46.
Productized Fusion → Oracle AI Data Platform pipeline. Curated BICC extracts for the most-asked Fusion ERP/HCM/SCM datasets, bronze→silver→gold medallion architecture, conformed COA/calendar/org/supplier/item dimensions, ready-made AR-aging/AP-aging/GL-balance/PO-backlog/Supplier-spend gold marts, and an Oracle Analytics Cloud (OAC) workbook bundle installable via OAC REST API. End-user consumption via OAC MCP (Preview) chat in Claude/Cline/Copilot. Same pattern shown in the official Oracle blog 'Bring Fusion Data into AIDP Workbench Using BICC', productized. Additive to and complementary with Oracle's managed Fusion data offerings — never positioned as a replacement.
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