feat: background task dispatch system with live UI panel

- agent/task_registry.py: file-based JSONL event registry (cross-process)
- agent/task_worker.py: autonomous LLM loop with weather/time/memory/web tools
- agent/dispatch_mcp.py: MCP tool exposing dispatch_task to the main agent
- agent/agent.py: registers dispatch toolset, polls task events → room data
- web: slide-out task panel (FAB button + badge), live step streaming via
  data channel topic 'tasks', status dots (running/completed/failed)
- Dockerfile: copies new task_*.py and dispatch_mcp.py files

The dispatch MCP runs in its own process; events flow through
/tmp/tasks/events.jsonl which the main agent tails every second and
forwards to the browser. Tasks run up to 10 LLM iterations with tool calls.

agent/dispatch_mcp.py

@@ -0,0 +1,58 @@
+"""Dispatch MCP server — lets Hope spawn background tasks.
+
+The main agent calls dispatch_task(description) when the user asks for
+something long-running. The tool returns immediately with a task ID; the
+actual work runs in a background asyncio task via TaskWorker.
+
+Communication with the main agent process happens via /tmp/tasks/events.jsonl
+(the file-based registry).
+"""
+from __future__ import annotations
+
+import asyncio
+import logging
+
+from mcp.server.fastmcp import FastMCP
+
+logger = logging.getLogger("voice-agent.dispatch")
+
+mcp = FastMCP("dispatch")
+
+
+@mcp.tool()
+async def dispatch_task(description: str) -> str:
+    """Spawn a background task to research or look something up.
+
+    Use this when the user asks you to do something that will take more than
+    a few seconds (research, look up news, multi-step investigation). The task
+    runs in parallel while you continue the conversation. When it completes,
+    the result will be delivered back to you automatically — you can tell the
+    user "I'll let you know when I find out."
+
+    Returns a short confirmation with the task ID.
+    """
+    try:
+        from agent.task_registry import registry
+        from agent.task_worker import TaskWorker
+    except ImportError:
+        from task_registry import registry
+        from task_worker import TaskWorker
+
+    task = registry.create(description)
+    worker = TaskWorker(task.id, description)
+    asyncio.create_task(_run_worker(worker, task.id))
+    logger.info("Dispatched task %s: %s", task.id, description)
+    return f"Task {task.id} started. I'll report back when it's done."
+
+
+async def _run_worker(worker: "TaskWorker", task_id: str):
+    try:
+        from agent.task_registry import registry
+    except ImportError:
+        from task_registry import registry
+
+    try:
+        await worker.run()
+    except Exception as e:
+        logger.exception("Task %s crashed: %s", task_id, e)
+        registry.fail(task_id, str(e))