MrAssistant AI helps teams ship multilingual voice and agent experiences for business-to-consumer use cases: self-serve help, guided flows, and handoffs to human teams when needed. These docs stay high level: how the product fits together, what to plan for on the voice side, and why many B2C teams adopt an MCP-style integration layer so assistants stay maintainable as you add channels and capabilities.Documentation Index
Fetch the complete documentation index at: https://docs.mrassistant.ai/llms.txt
Use this file to discover all available pages before exploring further.
Get started
Quickstart
A simple mental model for going from idea to integrated experience.
MCP for B2C
Why a Model Context Protocol server matters for consumer-facing AI at scale.
Web and voice
How web, mobile, and realtime voice pieces fit together.
API reference
Technical reference generated from the public API description.
Build
Agents
What an agent represents and how you evolve it over time.
Knowledge and tools
Grounding content and extending behavior with controlled actions.
Voice and providers
Speech, language models, and provider choice at a glance.
Multilingual
Serving more than one language and locale with confidence.