This　paper　develops　distributed　algorithms　for　solving　Sylvester　equations.The　authors　transform　solving　Sylvester　equations　into　a　distributed　optimization　problem,unifying　all　eight　stan-dard　distributed　matrix　structures.Then　the　authors　propose　a　distributed　algorithm　to　find　the　least　squares　solution　and　achieve　an　explicit　linear　convergence　rate.These　results　are　obtained　by　carefully　choosing　the　step-size　of　the　algorithm,which　requires　particular　information　of　data　and　Laplacian　matrices.To　avoid　these　centralized　quantities,the　authors　further　develop　a　distributed　scaling　tech-nique　by　using　local　information　only.As　a　result,the　proposed　distributed　algorithm　along　with　the　distributed　scaling　design　yields　a　universal　method　for　solving　Sylvester　equations　over　a　multi-agent　network　with　the　constant　step-size　freely　chosen　from　configurable　intervals.Finally,the　authors　provide　three　examples　to　illustrate　the　effectiveness　of　the　proposed　algorithms.