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FPGAs are increasingly prevalent in cloud deployments, serving as Smart-NICs or network-attached accelerators. To facilitate the development of distributed applications with FPGAs, in this paper we propose ACCL+, an open-source, FPGA-based collective communication library. Portable across different platforms and supporting UDP, TCP, as well as RDMA, ACCL+ empowers FPGA applications to initiate direct FPGA-to-FPGA collective communication. Additionally, it can serve as a collective offload engine for CPU applications, freeing the CPU from networking tasks. It is user-extensible, allowing new collectives to be implemented and deployed without having to re-synthesize the entire design. We evaluated ACCL+ on an FPGA cluster with 100 Gb/s networking, comparing its performance against software MPI over RDMA. The results demonstrate ACCL+'s significant advantages for FPGA-based distributed applications and its competitive performance for CPU applications. We showcase ACCL+'s dual role with two use cases: as a collective offload engine to distribute CPU-based vector-matrix multiplication, and as a component in designing fully FPGA-based distributed deep-learning recommendation inference.