seismic-waveform-processing

name	seismic-waveform-processing
description	Process seismic waveform data including reading MinISEED/SAC files, extracting metadata, and visualizing earthquake signals.
license	MIT license
metadata	{"skill-author":"PJLab"}

Seismic Waveform Processing

Usage

1. MCP Server Definition

import asyncio
import json
from contextlib import AsyncExitStack
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._stack = AsyncExitStack()
            await self._stack.__aenter__()
            self.read, self.write, self.get_session_id = await self._stack.enter_async_context(self.transport)
            self.session_ctx = ClientSession(self.read, self.write)
            self.session = await self._stack.enter_async_context(self.session_ctx)
            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 hasattr(self, '_stack'):
                await self._stack.aclose()
            print("✓ already disconnect")
        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)}

2. Seismic Waveform Processing Workflow

This workflow processes seismic waveform data from MinISEED or SAC files.

Workflow Steps:

1. Read Waveform Data - Load seismic data from file
2. Extract Metadata - Retrieve station and instrument information
3. Visualize Waveform - Generate time-series plot

Implementation:

## 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()

Tool Descriptions

SeisOBS-Tool Server:

• read_mseed_file: Read waveform data from MinISEED file

  • Args:
    • data_path (str): Path or URL to MinISEED file
    • channel_idx (int): Channel index to read
  • Returns: Waveform time series data

• read_mseed_file_stats: Extract metadata from MinISEED file

  • Args:
    • data_path (str): Path or URL to MinISEED file
    • channel_idx (int): Channel index
    • outfile (str, optional): Output file path
  • Returns: Station metadata and instrument information

• plot_single_waveform: Generate waveform plot

  • Args:
    • data_path (str): Path or URL to MinISEED file
    • channel_idx (int): Channel index
    • outfile (str, optional): Output image path
    • starttime (str, optional): Plot start time
    • endtime (str, optional): Plot end time
  • Returns: Path to generated plot image

Input/Output

Input:

• data_path: Path or URL to seismic data file (MinISEED or SAC format)
• channel_idx: Index of the channel to process (0-based)
• starttime/endtime: Optional time window for plotting

Output:

• Waveform data array
• Metadata including station, sampling rate, start time
• Visualization image (PNG format)

Use Cases

• Earthquake signal analysis
• Seismic station quality control
• Waveform data preprocessing
• P-wave and S-wave identification
• Ground motion visualization

Performance Notes

• File formats: MinISEED (.mseed), SAC (.sac)
• Execution time: <5 seconds for typical earthquake recordings
• Data size: Handles files up to 100 MB efficiently