# Copyright (c) 2025 Agentspan
# Licensed under the MIT License. See LICENSE file in the project root for details.

"""MCP Weather — using Conductor's MCP system tasks for live weather.

Demonstrates the `mcp_tool()` function which uses Conductor's built-in
LIST_MCP_TOOLS and CALL_MCP_TOOL system tasks. The MCP test server
provides deterministic weather data, and the Conductor server handles all
MCP protocol communication — **no worker process needed**.

Flow:
    ListMcpTools → LLM (picks tool) → CallMcpTool → Final LLM

MCP Test Server Setup (mcp-testkit):
    pip install mcp-testkit

    # Start without auth:
    mcp-testkit --transport http

    # Or start with auth (requires storing the secret as a credential):
    mcp-testkit --transport http --auth <secret>

    # Store credentials via CLI or Agentspan UI:
    agentspan credentials set MCP_TEST_API_KEY <secret>

Requirements:
    - Conductor server with LLM support
    - mcp-testkit running on http://localhost:3001 (see setup above)
    - AGENTSPAN_SERVER_URL=http://localhost:6767/api as environment variable
    - AGENTSPAN_LLM_MODEL=openai/gpt-4o-mini as environment variable

Docker gotcha:
    When the AgentSpan server runs in Docker (e.g. `agentspan server start`),
    the *server* makes the MCP calls — not your local process.  The server
    resolves `localhost` to its own container loopback, not your host machine.

    Fix: use `host.docker.internal` so the container can reach your host:

        weather = mcp_tool(server_url="http://host.docker.internal:3001/mcp", ...)

    DNS rebinding protection: mcp-testkit rejects unknown Host headers with
    HTTP 421. If you hit this, patch the validation in the venv that the
    mcp-testkit process uses:

        sed -i '' \
          's/return Response("Invalid Host header", status_code=421)/return None/' \
          $(python -c "import mcp.server.transport_security as m; print(m.__file__)")
"""

from agentspan.agents import Agent, AgentRuntime, mcp_tool
from settings import settings

# Create MCP tool — Conductor discovers tools from mcp-testkit at runtime
# ${MCP_TEST_API_KEY} is resolved server-side from the credential store.
weather = mcp_tool(
    server_url="http://localhost:3001/mcp",
    name="weather_mcp",
    description="Weather and air quality tools via MCP, use it to get current and historical weather information for "
                "a city",
    headers={"Authorization": "Bearer ${MCP_TEST_API_KEY}"},
    credentials=["MCP_TEST_API_KEY"],
)

agent = Agent(
    name="weather_mcp_agent",
    model=settings.llm_model,
    max_tokens=10240,
    tools=[weather],
    instructions=(
        "You are a weather assistant. Use the available MCP tools "
        "to answer questions about weather conditions around the world."
        "when asked get the current temperature in F"
        "use the tools provided"
    ),
)


if __name__ == "__main__":
    with AgentRuntime() as runtime:
        result = runtime.run(agent, "What's the weather like in San Francisco (CA) right now?")
        result.print_result()

        # Production pattern:
        # 1. Deploy once during CI/CD:
        # runtime.deploy(agent)
        # CLI alternative:
        # agentspan deploy --package examples.04_mcp_weather
        #
        # 2. In a separate long-lived worker process:
        # runtime.serve(agent)