Context : Galaxy clusters trace the highest density peaks in the large-scale structure of the Universe .
Their clustering provides a powerful probe that can be exploited in combination with cluster mass measurements to strengthen the cosmological constraints provided by cluster number counts .

Aims : We investigate the spatial properties of a homogeneous sample of X-ray selected galaxy clusters from the XXL survey , the largest programme carried out by the XMM-Newton satellite .
The measurements are compared to \Lambda -cold dark matter predictions , and used in combination with self-calibrated mass scaling relations to constrain the effective bias of the sample , b _ { eff } , and the matter density contrast , \Omega _ { M } .

Methods : We measured the angle-averaged two-point correlation function of the XXL cluster sample .
The analysed catalogue consists of 182 X-ray selected clusters from the XXL second data release , with median redshift \langle z \rangle = 0.317 and median mass \langle M _ { 500 } \rangle \simeq 1.3 \cdot 10 ^ { 14 } M _ { \odot } .
A Markov chain Monte Carlo analysis is performed to extract cosmological constraints using a likelihood function constructed to be independent of the cluster selection function .

Results : Modelling the redshift-space clustering in the scale range 10 < r [ h ^ { -1 } \mbox { Mpc } ] < 40 , we obtain \Omega _ { M } = 0.27 _ { -0.04 } ^ { +0.06 } and b _ { eff } = 2.73 _ { -0.20 } ^ { +0.18 } .
This is the first time the two-point correlation function of an X-ray selected cluster catalogue at such relatively high redshifts and low masses has been measured .
The XXL cluster clustering appears fully consistent with standard cosmological predictions .
The analysis presented in this work demonstrates the feasibility of a cosmological exploitation of the XXL cluster clustering , paving the way for a combined analysis of XXL cluster number counts and clustering .

Conclusions :