This　article　presents　the　adaptive　tracking　control　scheme　of　nonlinear　multiagent　systems　under　a　directed　graph　and　state　constraints.　In　this　article,　the　integral　barrier　Lyapunov　functionals　(iBLFs)　are　introduced　to　overcome　the　conservative　limitation　of　the　barrier　Lyapunov　function　with　error　variables,　relax　the　feasibility　conditions,　and　simultaneously　solve　state　constrained　and　coupling　terms　of　the　communication　errors　between　agents.　An　adaptive　distributed　controller　was　designed　based　on　iBLF　and　backstepping　method,　and　iBLF　was　differentiated　by　means　of　the　integral　mean　value　theorem.　At　the　same　time,　the　properties　of　neural　network　are　used　to　approximate　the　unknown　terms,　and　the　stability　of　the　systems　is　proven　by　the　Lyapunov　stability　theory.　This　scheme　can　not　only　ensure　that　the　output　of　all　the　followers　meets　the　output　trajectory　of　the　leader　but　also　make　the　state　variables　not　violate　the　constraint　bounds,　and　all　the　closed-loop　signals　are　bounded.　Finally,　the　efficiency　of　the　proposed　controller　is　revealed.