Pipecat MCP server for your AI agents
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<h1><div align="center"> <img alt="Pipecat MCP Server" width="300px" height="auto" src="https://github.com/pipecat-ai/pipecat-mcp-server/raw/refs/heads/main/pipecat.png"> </div></h1> [](https://pypi.org/project/pipecat-ai-mcp-server) [](https://discord.gg/pipecat) # Pipecat MCP Server Pipecat MCP Server gives your AI agents a voice using [Pipecat](https://github.com/pipecat-ai/pipecat). It should work with any [MCP](https://modelcontextprotocol.io/)-compatible client: The Pipecat MCP Server exposes **voice-related** and **screen capture** tools to MCP-compatible clients, but **it does not itself provide microphone or speaker access**. Audio input/output is handled by a **separate audio/video transport**, such as: - **Pipecat Playground** (local browser UI) - **Daily** (WebRTC room) - **Phone providers** (Twilio, Telnyx, etc.) > **MCP clients like Cursor, Claude Code, and Codex control the agent, but they are not audio devices.** > To hear, speak or see, you must connect via one of the audio transports. <p align="center"><video src="https://github.com/user-attachments/assets/0ad14e37-2de7-46df-870a-167aa667df16" width="500" controls></video></p> ## 🧭 Getting started ### Prerequisites - Python 3.10 or later - [uv](https://docs.astral.sh/uv/getting-started/installation/) package manager By default, the voice agent uses local models (no API keys required): [Faster Whisper](https://github.com/SYSTRAN/faster-whisper) for speech-to-text and [Kokoro](https://github.com/hexgrad/kokoro) for text-to-speech. The Whisper models are approximately 1.5 GB and are downloaded automatically on the first connection, so the initial startup may take a moment. ### Installation ```bash uv tool install pipecat-ai-mcp-server ``` This will install the `pipecat-mcp-server` tool. If you want to use different services or modify the Pipecat pipeline somehow,…
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