This is not a measurement error model, this is a missing data model. Measurement error models are specified in brms with me(), not mi().
See Predictors with Measurement Error in brms Models — me • brms for examples. I’d guess this will match your use case reasonably well.
There are a bunch of forum posts here e.g.: Using posteriors as new priors discussing potential drawbacks of this approximation (compared to a full joint model), so consider yourself warned :-)
Best of luck with your project!