This topic covers voice and speech AI platforms that power clinical voice assistants and assistive workflows — from real‑time speech recognition and text‑to‑speech to telephony, meeting agents and transcription pipelines. It focuses on the integration layer (MCP servers and connectors) that lets healthcare and accessibility applications combine STT/TTS engines, voice cloning/localization, telephony APIs and meeting transcripts into compliant, low‑latency experiences. As of 2025‑11‑26, voice interfaces have moved from experimental demos to production components in telehealth, clinical documentation, remote monitoring and assistive technology. That shift raises practical priorities: accuracy of medical transcription, latency for conversational triage, PHI handling and consent, provenance/anti‑misuse controls around voice cloning, and predictable integration via interoperable servers. Key tools and roles described here include: VoiceMode — bridges microphone input to Claude and OpenAI‑compatible assistants for natural voice conversations; ElevenLabs and Kokoro TTS — multi‑voice TTS servers for generating audio and structured voiceovers; Transcribe — MCP server for fast local audio/video transcription to feed LLMs and clinical documentation; joinly — middleware enabling AI agents to join meetings with voice, chat and transcript access; Cartesia — voice platform for TTS and voice cloning/localization; Twilio and Telnyx — telephony and messaging MCP servers for call/SMS-based workflows. When evaluating platforms, emphasize accuracy, on‑device vs cloud tradeoffs, security/HIPAA posture, consent and anti‑spoofing, auditability, and operational factors (latency, cost, multi‑voice support). Combining these MCP connectors lets teams prototype clinical voice assistants while maintaining control over data flows and compliance.