Seismic Waveform Processing

import asyncio
import json
from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession

class SeismicClient:
    """SeisOBS-Tool MCP Client"""

    def __init__(self, server_url: str, api_key: str):
        self.server_url = server_url
        self.api_key = api_key
        self.session = None

    async def connect(self):
        """Establish connection and initialize session"""
        try:
            self.transport = streamablehttp_client(
                url=self.server_url,
                headers={"SCP-HUB-API-KEY": self.api_key}
            )
            self.read, self.write, self.get_session_id = await self.transport.__aenter__()
            self.session_ctx = ClientSession(self.read, self.write)
            self.session = await self.session_ctx.__aenter__()
            await self.session.initialize()
            return True
        except Exception as e:
            print(f"✗ connect failure: {e}")
            return False

    async def disconnect(self):
        """Disconnect from server"""
        try:
            if self.session:
                await self.session_ctx.__aexit__(None, None, None)
            if hasattr(self, 'transport'):
                await self.transport.__aexit__(None, None, None)
        except Exception as e:
            print(f"✗ disconnect error: {e}")

    def parse_result(self, result):
        """Parse MCP tool call result"""
        try:
            if hasattr(result, 'content') and result.content:
                content = result.content[0]
                if hasattr(content, 'text'):
                    return json.loads(content.text)
            return str(result)
        except Exception as e:
            return {"error": f"parse error: {e}", "raw": str(result)}

## Initialize client
client = SeismicClient(
    "https://scp.intern-ai.org.cn/api/v1/mcp/33/SeisOBS-Tool",
    "<your-api-key>"
)

if not await client.connect():
    print("connection failed")
    exit()

## Input: Path to seismic data file (URL or local path)
data_path = "https://example.com/seismic_data.mseed"
channel_idx = 0  # Channel index to process

## Step 1: Read waveform data
result = await client.session.call_tool(
    "read_mseed_file",
    arguments={
        "data_path": data_path,
        "channel_idx": channel_idx
    }
)

waveform_data = client.parse_result(result)
print(f"Waveform data shape: {len(waveform_data['st'])} samples")

## Step 2: Extract metadata
result = await client.session.call_tool(
    "read_mseed_file_stats",
    arguments={
        "data_path": data_path,
        "channel_idx": channel_idx,
        "outfile": None
    }
)

metadata = client.parse_result(result)
print(f"Station: {metadata.get('station', 'N/A')}")
print(f"Sampling rate: {metadata.get('sampling_rate', 'N/A')} Hz")

## Step 3: Visualize waveform
result = await client.session.call_tool(
    "plot_single_waveform",
    arguments={
        "data_path": data_path,
        "channel_idx": channel_idx,
        "outfile": None,
        "starttime": None,
        "endtime": None
    }
)

plot_result = client.parse_result(result)
print(f"Waveform plot saved to: {plot_result['st']}")

await client.disconnect()