As　video　data　continues　to　grow,　the　burden　on　network　transmission　increases　significantly.　Efficient　video　compression　techniques　are　crucial　to　meet　the　rising　demand　for　multimedia　content.　In　this　letter,　we　propose　a　Multi-scale　Motion　Alignment　and　Frame　Reconstruction-based　Video　Codec　(MFVC)　for　efficient　video　compression.　MFVC　focuses　on　optimizing　the　motion　compensation　and　video　reconstruction　processes　within　a　deep　video　compression　framework.　First,　we　design　a　Multi-Scale　Motion　Alignment　Network　(MSMA-Net)　to　achieve　precise　motion　compensation,　which　extracts　multi-scale　features　from　video　frames　and　utilizes　flow　information　for　deformable　convolution.　Second,　we　design　a　Frame　Reconstruction　Network　(FR-Net)　to　recover　high-quality　video　frames,　which　utilizes　reference　information　for　feature　enhancement　without　additional　bitrate　consumption.　Moreover,　to　achieve　smooth　rate　adjustment,　we　introduce　a　feature　scaling　technique.　Experimental　results　show　that　MFVC　reduces　bitrate　by　7.86%/48.34%　compared　to　VVC　(VTM　13.2)　at　the　same　PSNR/MS-SSIM.