NavMCP integrates vision-language models with navigation foundation models through three communication channels — intent, observation, and memory — to enable long-horizon embodied exploration. The system reaches state-of-the-art performance on benchmarks including HM-EQA and EXPRESS-Bench and achieves 78.3% success on physical robot tasks, with gains growing substantially as task horizon lengthens.
