In this article, we investigate optimal transmission power allocation at a sensor equipped with the energy-harvesting technology for remote state estimation in wireless cyber-physical systems. The sensor has access to an energy harvester, which can collect energy from the external environment and is an everlasting but unreliable energy source compared with conventional batteries. For the wireless dropping communication channel, the packet dropout rates depend on both the signal-to-noise ratio and the transmission power used by the sensor. We formulate the problem of the optimal transmission power allocation to minimize the remote estimation error covariances as a Markov decision processes (MDPs) subject to energy constraint of the sensor. By analyzing the MDP algorithm, we show that an optimal deterministic and stationary transmission power policy exists. Moreover, we show that the optimal policy has a threshold-type structure. A numerical simulation is provided to illustrate the performance of the transmission power allocation algorithm.