station_crowd_forecast

Forecast MRT/LRT station crowdedness levels in 30-minute intervals to plan travel and avoid peak congestion.

Instructions

Get forecasted MRT/LRT station crowdedness levels in 30-minute intervals.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`trainLine`	Yes	Code of train network line (CCL, CEL, CGL, DTL, EWL, NEL, NSL, BPL, SLRT, PLRT, TEL)

Implementation Reference

src/index.ts:325-359 (handler)

The handler function for the 'station_crowd_forecast' tool. It extracts the 'trainLine' argument, makes an API call to LTA's PCDForecast endpoint, and returns the JSON response or an error message.

case "station_crowd_forecast": {
  const { trainLine } = request.params.arguments as {
    trainLine: string;
  };

  try {
    const response = await axios.get('https://datamall2.mytransport.sg/ltaodataservice/PCDForecast', {
      params: {
        TrainLine: trainLine
      },
      headers: {
        'AccountKey': process.env.LTA_API_KEY!,
        'accept': 'application/json'
      }
    });
    
    return {
      content: [{
        type: "text",
        text: JSON.stringify(response.data, null, 2)
      }]
    };
  } catch (error) {
    if (axios.isAxiosError(error)) {
      return {
        content: [{
          type: "text",
          text: `LTA API error: ${error.response?.data?.Message ?? error.message}`
        }],
        isError: true
      };
    }
    throw error;
  }
}

src/index.ts:117-127 (schema)

Input schema for the 'station_crowd_forecast' tool, defining the required 'trainLine' parameter with allowed enum values.

inputSchema: {
  type: "object",
  properties: {
    trainLine: {
      type: "string",
      description: "Code of train network line (CCL, CEL, CGL, DTL, EWL, NEL, NSL, BPL, SLRT, PLRT, TEL)",
      enum: ["CCL", "CEL", "CGL", "DTL", "EWL", "NEL", "NSL", "BPL", "SLRT", "PLRT", "TEL"]
    }
  },
  required: ["trainLine"]
}

src/index.ts:114-128 (registration)

Registration of the 'station_crowd_forecast' tool in the ListTools response, including name, description, and input schema.

{
  name: "station_crowd_forecast",
  description: "Get forecasted MRT/LRT station crowdedness levels in 30-minute intervals.",
  inputSchema: {
    type: "object",
    properties: {
      trainLine: {
        type: "string",
        description: "Code of train network line (CCL, CEL, CGL, DTL, EWL, NEL, NSL, BPL, SLRT, PLRT, TEL)",
        enum: ["CCL", "CEL", "CGL", "DTL", "EWL", "NEL", "NSL", "BPL", "SLRT", "PLRT", "TEL"]
      }
    },
    required: ["trainLine"]
  }
}]

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