Is it necessary to calculate VAR before Granger causality test so that we can have the lag length to be used in Granger causality test
Granger Causality can be defined as: "X is said to Granger-cause Y if Y can be better predicted using the histories of both X and Y than it can by using the history of Y alone." 1
or in other words: "A time series X is said to Granger-cause Y if it can be shown, usually through a series of t-tests and F-tests on lagged values of X (and with lagged values of Y also included), that those X values provide statistically significant information about future values of Y." Wikipedia
This is essentially what a vector autoregression model does.
Also wikipedia says: "Multivariate Granger causality analysis is usually performed by fitting a vector autoregressive model (VAR) to the time series."
Granger causality is therefore more a form of structurally summarizing VAR models.
For some more information: here
No need.From varGranger causality test unidirectional or bidirectional causality can be found out which fullfills the purpose of causality test.