Voice Assistant MCP Server

The Voice Assistant MCP Server bridges the gap between conversational AI and real‑world voice interactions by combining Twilio Voice, Deepgram’s speech‑to‑text and text‑to‑speech APIs, and OpenAI’s language models. It gives AI assistants like Claude the ability to make outbound calls, listen to human speech in real time, and respond with natural language—all while preserving the context required by Model Context Protocol (MCP) tooling. This makes it possible to automate HR workflows such as phone interviews, interview result notifications, and proactive candidate outreach without building custom telephony infrastructure.

At its core, the server exposes a set of MCP tools that orchestrate a call lifecycle. When a client invokes , the server initiates a Twilio Voice call to the target number, streams the audio through Twilio Media Streams to Deepgram for transcription, and feeds the resulting text into an OpenAI model. The model’s response is then converted back to speech by Deepgram and streamed back to the caller, creating a seamless conversational loop. The same pattern is used for other tools such as or , each tailored with dynamic prompts that reflect the purpose of the call.

Key capabilities include:

• WebSocket‑based media streaming that keeps latency low and allows the assistant to react instantly to user input.
• Dynamic prompt injection, enabling each call type to have context‑specific instructions that steer the LLM’s behavior.
• Advanced function calling for call management tasks (e.g., pause, hang up, transfer), giving developers fine‑grained control over the telephony flow.
• Comprehensive logging for debugging and compliance, capturing call metadata, transcriptions, and AI responses.
• Secure environment configuration, ensuring that Twilio and Deepgram credentials are never exposed in code.

Real‑world scenarios benefit greatly from this integration. HR teams can schedule automated interview calls, automatically deliver feedback to candidates, and even reach out to passive talent pools—all while maintaining a natural conversational tone. Beyond HR, the same architecture can power customer support bots, tele‑medicine triage calls, or any use case that requires a conversational AI to speak with humans over the phone.

For developers building MCP‑enabled assistants, this server provides a plug‑and‑play solution that abstracts away the complexities of telephony and speech processing. By simply adding the server’s configuration to a tool‑enabled client like Claude Desktop, developers can immediately unlock voice capabilities in their workflows, enabling richer, multimodal interactions without writing low‑level telephony code.