csmar_query_count

Instructions

Implementation Reference

• src/index.js:549-556 (schema)

  Input schema definition for csmar_query_count tool, describing the required table_name and optional columns, condition, start_time, end_time parameters.

  description: '查询满足条件的记录数量',
  inputSchema: {
      table_name: z.string().describe('表名称'),
      columns: z.array(z.string()).optional().describe('字段列表'),
      condition: z.string().optional().describe('查询条件'),
      start_time: z.string().optional().describe('开始时间'),
      end_time: z.string().optional().describe('结束时间'),
  },

• src/index.js:546-572 (registration)

  Registration of the 'csmar_query_count' tool with the MCP server, including description, input schema, and handler.

  server.registerTool(
      'csmar_query_count',
      {
          description: '查询满足条件的记录数量',
          inputSchema: {
              table_name: z.string().describe('表名称'),
              columns: z.array(z.string()).optional().describe('字段列表'),
              condition: z.string().optional().describe('查询条件'),
              start_time: z.string().optional().describe('开始时间'),
              end_time: z.string().optional().describe('结束时间'),
          },
      },
      async ({ table_name, columns = [], condition = '', start_time, end_time }) => {
          try {
              const loginResult = await ensureLogin();
              if (!loginResult.success) {
                  return { content: [{ type: 'text', text: JSON.stringify(loginResult, null, 2) }], isError: true };
              }
              
              const client = await initPythonClient();
              const result = await client.call('query_count', { table_name, columns, condition, start_time, end_time });
              return { content: [{ type: 'text', text: JSON.stringify(result, null, 2) }] };
          } catch (error) {
              return { content: [{ type: 'text', text: `查询数量错误: ${error.message}` }], isError: true };
          }
      }
  );

• src/index.js:558-571 (handler)

  Handler function for csmar_query_count that ensures login, initializes the Python client, and calls 'query_count' action on the Python client.

  async ({ table_name, columns = [], condition = '', start_time, end_time }) => {
      try {
          const loginResult = await ensureLogin();
          if (!loginResult.success) {
              return { content: [{ type: 'text', text: JSON.stringify(loginResult, null, 2) }], isError: true };
          }
          
          const client = await initPythonClient();
          const result = await client.call('query_count', { table_name, columns, condition, start_time, end_time });
          return { content: [{ type: 'text', text: JSON.stringify(result, null, 2) }] };
      } catch (error) {
          return { content: [{ type: 'text', text: `查询数量错误: ${error.message}` }], isError: true };
      }
  }

• src/python_client.py:266-282 (helper)

  Python helper method 'query_count' on CSMARClient that calls the CSMAR SDK's queryCount method and returns the result.

  def query_count(self, columns: list, condition: str, table_name: str,
                 start_time: Optional[str] = None, end_time: Optional[str] = None) -> Dict[str, Any]:
      try:
          csmar = self._ensure_csmar()
          count = csmar.queryCount(columns, condition, table_name, start_time, end_time)
          return {"success": True, "table": table_name, "count": int(count) if count else 0}
      except Exception as e:
          return {"success": False, "error": f"查询数量失败: {str(e)}"}
  
  def query(self, columns: list, condition: str, table_name: str,
           start_time: Optional[str] = None, end_time: Optional[str] = None,
           format: str = "json", limit: Optional[int] = None) -> Dict[str, Any]:
      try:
          csmar = self._ensure_csmar()
          if format == "dataframe":
              data = csmar.query_df(columns, condition, table_name, start_time, end_time)
              result = data.to_dict('records') if hasattr(data, 'to_dict') else data

• src/python_client.py:320-323 (helper)

  Command dispatch registration mapping the 'query_count' action string to the Python client's query_count method.

  "query_count": lambda: client.query_count(
      params.get("columns", []), params.get("condition", ""), params.get("table_name", ""),
      params.get("start_time"), params.get("end_time")
  ),