feat: add get_weather MCP tool using wttr.in API

- New agent/weather_mcp.py: stdio MCP server with get_weather(location)
  that returns a short conversational summary (temp, conditions, high/low)
- Register weather toolset in build_mcp_toolsets() alongside web-access
- Update system prompt with Weather section

agent/agent.py

@@ -63,12 +63,17 @@ SYSTEM_PROMPT = textwrap.dedent("""\
 
     # Web access
     You have web_search and web_scrape tools. Use them when the user asks about
-    current events, recent news, prices, weather, sports scores, or anything
+    current events, recent news, prices, sports scores, or anything
     that may have changed since your training data. Search first, then scrape
     a result only if you need more detail. Answer from what you find, in your
     normal conversational style — don't cite sources formally, just mention the
     source naturally ("according to..."). If a search comes up empty, say so
     briefly and move on.
+
+    # Weather
+    You can check the weather for any location. Use get_weather when the user
+    asks about current conditions, temperature, or forecasts. It returns a
+    short summary — relay it naturally in your own words.
 """)
 
 
@@ -178,6 +183,21 @@ def build_mcp_toolsets() -> list[mcp.MCPToolset]:
         )
         logger.info("Web-access MCP toolset enabled (Firecrawl at %s)", FIRECRAWL_BASE)
 
+    python_bin = os.path.join(os.path.dirname(os.path.abspath(__file__)), ".venv", "bin", "python")
+    weather_mcp_script = os.path.join(os.path.dirname(os.path.abspath(__file__)), "weather_mcp.py")
+    toolsets.append(
+        mcp.MCPToolset(
+            id="weather",
+            mcp_server=mcp.MCPServerStdio(
+                command=python_bin,
+                args=[weather_mcp_script],
+                env={**os.environ},
+                client_session_timeout_seconds=30,
+            ),
+        )
+    )
+    logger.info("Weather MCP toolset enabled (wttr.in)")
+
     extra = os.environ.get("EXTRA_MCP_SERVERS", "")
     if extra:
         try:

agent/voice_agent.egg-info/PKG-INFO

@@ -0,0 +1,9 @@
+Metadata-Version: 2.4
+Name: voice-agent
+Version: 0.1.0
+Summary: Real-time voice assistant: Azure STT/TTS + Gemma LLM via LiveKit Agents
+Requires-Python: <3.15,>=3.10
+Requires-Dist: livekit-agents[mcp]~=1.7
+Requires-Dist: livekit-plugins-azure~=1.7
+Requires-Dist: livekit-plugins-openai~=1.7
+Requires-Dist: python-dotenv

agent/voice_agent.egg-info/SOURCES.txt

@@ -0,0 +1,6 @@
+pyproject.toml
+voice_agent.egg-info/PKG-INFO
+voice_agent.egg-info/SOURCES.txt
+voice_agent.egg-info/dependency_links.txt
+voice_agent.egg-info/requires.txt
+voice_agent.egg-info/top_level.txt

agent/voice_agent.egg-info/dependency_links.txt

@@ -0,0 +1 @@
+

agent/voice_agent.egg-info/requires.txt

@@ -0,0 +1,4 @@
+livekit-agents[mcp]~=1.7
+livekit-plugins-azure~=1.7
+livekit-plugins-openai~=1.7
+python-dotenv

agent/voice_agent.egg-info/top_level.txt

@@ -0,0 +1 @@
+

agent/weather_mcp.py

@@ -0,0 +1,88 @@
+"""Weather MCP server — exposes a get_weather tool backed by wttr.in.
+
+Runs over stdio inside the voice container. The agent attaches it via
+MCPServerStdio, so the LLM can call get_weather during a conversation to
+report current conditions and today's forecast for any location.
+
+Backed by wttr.in (no API key needed):
+  - GET https://wttr.in/{location}?format=j1  -> full JSON weather report
+
+The tool returns a short, conversational summary suitable for speech
+(1-2 sentences), not raw data.
+"""
+
+from __future__ import annotations
+
+import os
+
+import httpx
+from mcp.server.fastmcp import FastMCP
+
+WTTR_BASE = os.environ.get("WTTR_BASE", "https://wttr.in").rstrip("/")
+
+mcp = FastMCP("weather")
+
+
+def _summarize(data: dict, location: str) -> str:
+    """Build a short spoken-style weather summary from wttr.in j1 JSON."""
+    current = data.get("current_condition", [{}])[0] or {}
+    area = data.get("nearest_area", [{}])[0] or {}
+
+    city = (area.get("areaName", [{}])[0].get("value") or location).strip()
+    temp_c = current.get("temp_C")
+    feels_c = current.get("FeelsLikeC")
+    desc = (current.get("weatherDesc", [{}])[0].get("value") or "").strip().lower()
+
+    astronomy = data.get("astronomy", [{}])[0] or {}
+    sunrise = astronomy.get("sunrise", "")
+    sunset = astronomy.get("sunset", "")
+
+    today = (data.get("weather") or [None])[0] or {}
+    high_c = today.get("maxtempC")
+    min_c = today.get("mintempC")
+
+    parts: list[str] = []
+
+    if temp_c is not None:
+        lead = f"It's {temp_c} degrees and {desc or 'clear'} in {city}"
+        if feels_c is not None and feels_c != temp_c:
+            lead += f", feels like {feels_c}"
+        parts.append(lead + ".")
+
+    if high_c is not None and min_c is not None:
+        parts.append(f"Today's high is {high_c} and the low is {min_c}.")
+
+    if sunrise and sunset:
+        parts.append(f"Sunrise was at {sunrise} and sunset is at {sunset}.")
+
+    return " ".join(parts) or f"I have no detailed weather for {city} right now."
+
+
+@mcp.tool()
+async def get_weather(location: str) -> str:
+    """Get the current weather and today's forecast for a location.
+
+    Use this when the user asks about current conditions, temperature,
+    or the forecast for a place. Returns a short conversational summary
+    suitable for reading aloud (1-2 sentences).
+    """
+    try:
+        async with httpx.AsyncClient(timeout=30) as client:
+            resp = await client.get(
+                f"{WTTR_BASE}/{location}?format=j1",
+                headers={"User-Agent": "curl/8.0"},
+            )
+            resp.raise_for_status()
+            data = resp.json()
+    except Exception:  # noqa: BLE001
+        return "I couldn't get the weather for that location"
+
+    try:
+        summary = _summarize(data, location)
+    except Exception:  # noqa: BLE001
+        return "I couldn't get the weather for that location"
+    return summary
+
+
+if __name__ == "__main__":
+    mcp.run(transport="stdio")