get_charge_config

Instructions

Get battery charging configuration for a specific Alpha ESS system.
Returns structured configuration with clear period definitions and status.
If no serial provided, auto-selects if only one system exists.

Args:
    serial: The serial number of the Alpha ESS system (optional)
    
Returns:
    dict: Enhanced response with structured charging configuration

Implementation Reference

• main.py:665-733 (handler)

  The primary handler function for the 'get_charge_config' tool. It handles serial auto-discovery, calls the Alpha ESS API via client.getChargeConfigInfo, structures the response using helpers, and returns an enhanced standardized response.

  @mcp.tool()
  async def get_charge_config(serial: Optional[str] = None) -> dict[str, Any]:
      """
      Get battery charging configuration for a specific Alpha ESS system.
      Returns structured configuration with clear period definitions and status.
      If no serial provided, auto-selects if only one system exists.
      
      Args:
          serial: The serial number of the Alpha ESS system (optional)
          
      Returns:
          dict: Enhanced response with structured charging configuration
      """
      client = None
      try:
          # Auto-discover serial if not provided
          if not serial:
              serial_info = await get_default_serial()
              if not serial_info['success'] or not serial_info['serial']:
                  return create_enhanced_response(
                      success=False,
                      message=f"Serial auto-discovery failed: {serial_info['message']}",
                      raw_data=None,
                      data_type="config",
                      metadata={"available_systems": serial_info.get('systems', [])}
                  )
              serial = serial_info['serial']
  
          app_id, app_secret = get_alpha_credentials()
          client = alphaess(app_id, app_secret)
  
          # Get charge config
          config = await client.getChargeConfigInfo(serial)
  
          # Structure the config data
          structured = structure_config_data(config, "charge")
  
          return create_enhanced_response(
              success=True,
              message=f"Successfully retrieved charge config for {serial}",
              raw_data=config,
              data_type="config",
              serial_used=serial,
              metadata={
                  "config_type": "battery_charging",
                  "total_periods": 2,
                  "units": {"soc": "%", "time": "HH:MM"}
              },
              structured_data=structured
          )
  
      except ValueError as e:
          return create_enhanced_response(
              success=False,
              message=f"Configuration error: {str(e)}",
              raw_data=None,
              data_type="config"
          )
      except Exception as e:
          return create_enhanced_response(
              success=False,
              message=f"Error retrieving charge config: {str(e)}",
              raw_data=None,
              data_type="config"
          )
      finally:
          if client:
              await client.close()

• models.py:42-47 (schema)

  Dataclass schema defining the structured output format for charge configuration, used in the tool's structured_data response.

  class ChargeConfig:
      enabled: bool
      periods: List[ConfigPeriod]
      charge_limit_soc: int
      units: Dict[str, str]

• main.py:665-665 (registration)

  FastMCP decorator registering the get_charge_config function as a tool, which also auto-generates input schema from function signature and docstring.

  @mcp.tool()

• main.py:135-177 (helper)

  Helper function that transforms raw API charge config data into the structured ChargeConfig dataclass instance used by the tool.

  def structure_config_data(raw_data: Dict[str, Any], config_type: str) -> Union[ChargeConfig, DischargeConfig, Dict]:
      """Structure configuration data with better field names"""
      if config_type == "charge":
          return ChargeConfig(
              enabled=bool(raw_data.get('gridCharge', 0)),
              periods=[
                  ConfigPeriod(
                      period=1,
                      start_time=raw_data.get('timeChaf1', '00:00'),
                      end_time=raw_data.get('timeChae1', '00:00'),
                      active=raw_data.get('timeChaf1', '00:00') != '00:00' or raw_data.get('timeChae1', '00:00') != '00:00'
                  ),
                  ConfigPeriod(
                      period=2,
                      start_time=raw_data.get('timeChaf2', '00:00'),
                      end_time=raw_data.get('timeChae2', '00:00'),
                      active=raw_data.get('timeChaf2', '00:00') != '00:00' or raw_data.get('timeChae2', '00:00') != '00:00'
                  )
              ],
              charge_limit_soc=raw_data.get('batHighCap', 100),
              units={"soc": "%", "time": "HH:MM"}
          )
      elif config_type == "discharge":
          return DischargeConfig(
              enabled=bool(raw_data.get('ctrDis', 0)),
              periods=[
                  ConfigPeriod(
                      period=1,
                      start_time=raw_data.get('timeDisf1', '00:00'),
                      end_time=raw_data.get('timeDise1', '00:00'),
                      active=raw_data.get('timeDisf1', '00:00') != '00:00' or raw_data.get('timeDise1', '00:00') != '00:00'
                  ),
                  ConfigPeriod(
                      period=2,
                      start_time=raw_data.get('timeDisf2', '00:00'),
                      end_time=raw_data.get('timeDise2', '00:00'),
                      active=raw_data.get('timeDisf2', '00:00') != '00:00' or raw_data.get('timeDise2', '00:00') != '00:00'
                  )
              ],
              discharge_limit_soc=raw_data.get('batUseCap', 10),
              units={"soc": "%", "time": "HH:MM"}
          )
      return raw_data