We present a hybrid solver (called ) that exploits the potentiality of a Constraint Programming (CP) environment (Gecode) and of a Local Search (LS) framework (EasyLocal ++). allows to easily develop and use hybrid meta-heuristic combining CP and LS phases (in particular Large Neighborhood Search). We tested some hybrid algorithms on different instances of the Asymmetric Traveling Salesman Problem: even if only naive LS strategies have been used, our meta-heuristics improve the standard CP search, in terms of both goodness of the solution reached and execution time. will be integrated into a more general tool to solve Constraint Satisfaction/Optimization Problems. Moreover, it can be seen as a new library for approximate and efficient searching in Gecode.