  Quantum metrology offers a quadratic advantage over classical approaches to
parameter estimation problems by utilizing entanglement and nonclassicality.
However, the hurdle of actually implementing the necessary quantum probe states
and measurements, which vary drastically for different metrological scenarios,
is usually not taken into account. We show that for a wide range of tasks in
metrology, 2D cluster states (a particular family of states useful for
measurement-based quantum computation) can serve as flexible resources that
allow one to efficiently prepare any required state for sensing, and perform
appropriate (entangled) measurements using only single qubit operations.
Crucially, the overhead in the number of qubits is less than quadratic, thus
preserving the quantum scaling advantage. This is ensured by using a
compression to a logarithmically sized space that contains all relevant
information for sensing. We specifically demonstrate how our method can be used
to obtain optimal scaling for phase and frequency estimation in local
estimation problems, as well as for the Bayesian equivalents with Gaussian
priors of varying widths. Furthermore, we show that in the paradigmatic case of
local phase estimation 1D cluster states are sufficient for optimal state
preparation and measurement.
