Release v1.3.0: AI feature flag and MCP server

- Add AI_FEATURES_ENABLED config flag to gate AI/natural-language features
- Conditionally register /api/ask router based on AI_FEATURES_ENABLED
- Add GET /api/config/features endpoint for frontend feature detection
- Update frontend to hide Ask panel when AI features are disabled
- Implement standalone MCP server (backend/mcp_server.py) with tools:
  * search_events, get_event, get_summary, ask
- Add mcp dependency to requirements.txt
- Update .env.example, AGENTS.md, and ROADMAP.md
- Bump VERSION to 1.3.0

AGENTS.md

@@ -6,28 +6,34 @@ AOC is a FastAPI microservice that ingests Microsoft Entra (Azure AD) audit logs
 
 ## Technology Stack
 
-- **Runtime**: Python 3.11
-- **Web Framework**: FastAPI + Uvicorn
+- **Runtime**: Python 3.11 (3.14 for tests)
+- **Web Framework**: FastAPI + Uvicorn (Gunicorn in production)
 - **Database**: MongoDB (PyMongo)
-- **Frontend**: Vanilla HTML/CSS/JS (served as static files from `backend/frontend/`)
+- **Frontend**: Alpine.js + HTML/CSS (served as static files from `backend/frontend/`)
 - **Authentication**: Optional OIDC Bearer token validation against Microsoft Entra (using `python-jose` and MSAL.js on the frontend)
-- **External APIs**: Microsoft Graph API, Office 365 Management Activity API
-- **Deployment**: Docker Compose
+- **External APIs**: Microsoft Graph API, Office 365 Management Activity API, Azure OpenAI / MS Foundry
+- **Deployment**: Docker Compose (dev), Docker Compose + nginx (prod)
+- **CI/CD**: Gitea Actions (lint + test + Docker build + release)
 
 ## Project Structure
 
 ```
 backend/
   main.py              # FastAPI app, router registration, background periodic fetch
-  config.py            # Environment-based configuration (loads .env)
+  config.py            # Pydantic Settings configuration (loads .env)
   database.py          # MongoClient setup (db = micro_soc, collection = events)
   auth.py              # OIDC Bearer token validation, JWKS caching, role/group checks
   requirements.txt     # Python dependencies
-  Dockerfile           # python:3.11-slim image
+  Dockerfile           # python:3.11-slim image, non-root user, version baked at build
+  mcp_server.py        # Standalone MCP server for Claude Desktop / Cursor integration
   routes/
     fetch.py           # GET /api/fetch-audit-logs, run_fetch()
-    events.py          # GET /api/events, GET /api/filter-options
-    config.py          # GET /api/config/auth
+    events.py          # GET /api/events, GET /api/filter-options, PATCH tags, POST comments
+    config.py          # GET /api/config/auth, GET /api/config/features
+    ask.py             # POST /api/ask — natural language query with LLM
+    health.py          # GET /health, GET /metrics
+    rules.py           # Rule-based alerting endpoints
+    webhooks.py        # Microsoft Graph change notification webhooks
   graph/
     auth.py            # Client credentials token acquisition for Graph
     audit_logs.py      # Fetch and enrich directory audit logs from Graph
@@ -41,7 +47,7 @@ backend/
   mappings.yml         # User-editable category labels and summary templates
   maintenance.py       # CLI for re-normalization and deduplication of stored events
   frontend/
-    index.html         # Single-page UI with filters, pagination, raw-event modal
+    index.html         # Single-page UI with filters, pagination, ask panel, raw-event modal
     style.css          # Dark-themed stylesheet
 ```
 
@@ -60,6 +66,9 @@ Key variables:
 - `AUTH_ALLOWED_ROLES`, `AUTH_ALLOWED_GROUPS` — comma-separated access control lists
 - `ENABLE_PERIODIC_FETCH`, `FETCH_INTERVAL_MINUTES` — background ingestion scheduler
 - `MONGO_ROOT_USERNAME`, `MONGO_ROOT_PASSWORD`, `MONGO_PORT` — used by Docker Compose for MongoDB
+- `AI_FEATURES_ENABLED` — set `false` to completely disable AI endpoints and UI (default `true`)
+- `LLM_API_KEY`, `LLM_BASE_URL`, `LLM_MODEL`, `LLM_MAX_EVENTS`, `LLM_TIMEOUT_SECONDS` — LLM provider settings
+- `LLM_API_VERSION` — required for Azure OpenAI / MS Foundry endpoints
 
 ## Build and Run Commands
 
@@ -87,35 +96,81 @@ uvicorn main:app --reload --host 0.0.0.0 --port 8000
 ## API Endpoints
 
 - `GET /api/fetch-audit-logs?hours=168` — pulls last N hours (capped at 720 / 30 days) from all sources, normalizes, dedupes, and upserts into MongoDB
-- `GET /api/events` — list stored events with filters (`service`, `actor`, `operation`, `result`, `start`, `end`, `search`) and pagination (`page`, `page_size`)
+- `GET /api/events` — list stored events with filters (`service`, `actor`, `operation`, `result`, `start`, `end`, `search`) and cursor-based pagination
 - `GET /api/filter-options` — best-effort distinct values for UI dropdowns
 - `GET /api/config/auth` — auth configuration exposed to the frontend
+- `GET /api/config/features` — feature flags (`ai_features_enabled`)
+- `POST /api/ask` — natural language query; returns LLM narrative + referenced events (only when `AI_FEATURES_ENABLED=true`)
+- `GET /health` — liveness probe with DB connectivity
+- `GET /metrics` — Prometheus metrics
+
+## MCP Server
+
+A standalone MCP server (`backend/mcp_server.py`) exposes audit log tools for Claude Desktop, Cursor, and other MCP clients.
+
+Available tools:
+- `search_events` — Search by entity, service, operation, result, time range
+- `get_event` — Retrieve a single event by ID (raw JSON)
+- `get_summary` — Aggregated counts by service, operation, result, actor
+- `ask` — Natural language question (returns recent events + guidance)
+
+**Claude Desktop config** (`~/.config/claude/claude_desktop_config.json`):
+```json
+{
+  "mcpServers": {
+    "aoc": {
+      "command": "python",
+      "args": ["/path/to/aoc/backend/mcp_server.py"],
+      "env": {"MONGO_URI": "mongodb://root:example@localhost:27017/"}
+    }
+  }
+}
+```
+
+The MCP server imports `database.py` directly and does not go through the FastAPI layer, so it shares the same MongoDB connection but bypasses auth.
+
+## AI Feature Flag
+
+Set `AI_FEATURES_ENABLED=false` in `.env` to:
+- Prevent the `ask` router from being registered in FastAPI
+- Hide the "Ask a question" panel in the frontend
+- Return `ai_features_enabled: false` from `/api/config/features`
+
+This is intended for the open-core monetization split: core features (ingestion, filtering, search, export) are always available; premium AI features (NLQ, MCP) can be disabled.
 
 ## Code Conventions
 
 - Python modules use absolute imports within the `backend/` package (e.g., `from graph.auth import get_access_token`). When running locally, ensure the working directory is `backend/` so these resolve correctly.
-- No formal formatter or linter is configured. Keep changes consistent with the existing style: simple functions, explicit exception handling, and informative docstrings.
-- The frontend is a single HTML file with inline JavaScript. It relies on the MSAL.js CDN (`https://alcdn.msauth.net/browser/2.37.0/js/msal-browser.min.js`).
+- The project uses `ruff` for linting and formatting. Run `ruff check . && ruff format .` before committing.
+- Keep changes consistent with the existing style: simple functions, explicit exception handling, and informative docstrings.
+- The frontend is a single HTML file with inline JavaScript and Alpine.js.
 
 ## Testing
 
-There are currently **no automated tests** in this repository. When adding new features or bug fixes, verify behavior manually:
+Tests run with pytest and mongomock (no real MongoDB required):
 
-1. Start the server (Docker Compose or local uvicorn).
-2. Run a smoke test:
-   ```bash
-   curl http://localhost:8000/api/events
-   curl http://localhost:8000/api/fetch-audit-logs
-   ```
-3. Open http://localhost:8000 in a browser, apply filters, paginate, and click "View raw event".
+```bash
+cd backend
+python -m venv .venv_test
+source .venv_test/bin/activate
+pip install -r requirements.txt
+pytest tests/ -q
+```
+
+When adding new features or bug fixes, add or update tests in `backend/tests/`. The test suite covers:
+- Event normalization and deduplication
+- Auth middleware and token validation
+- API endpoints (`/api/events`, `/api/fetch-audit-logs`, `/api/ask`)
+- NLQ time range extraction, entity extraction, query building
 
 ## Security Considerations
 
-- **Secrets**: `CLIENT_SECRET` and other credentials come from `.env`. Never commit `.env`.
+- **Secrets**: `CLIENT_SECRET`, `LLM_API_KEY`, and other credentials come from `.env`. Never commit `.env`.
 - **Auth validation**: When `AUTH_ENABLED=true`, the backend fetches JWKS from `https://login.microsoftonline.com/{AUTH_TENANT_ID}/v2.0/.well-known/openid-configuration`, caches keys for 1 hour, and validates tenant/issuer claims. Tokens are decoded without strict signature verification (`jwt.get_unverified_claims`), so the tenant and issuer checks are the primary gate.
 - **Role/Group gating**: Access is allowed if the token’s `roles` intersect `AUTH_ALLOWED_ROLES` or `groups` intersect `AUTH_ALLOWED_GROUPS`. If neither list is configured, all authenticated users are allowed.
 - **Pagination limits**: `page_size` is clamped to a maximum of 500 to prevent large queries.
 - **Fetch window cap**: `hours` is clamped to 720 (30 days) to avoid runaway API calls.
+- **MCP server**: The MCP server bypasses auth entirely. Only run it in trusted environments or behind a VPN.
 
 ## Maintenance and Operations