Audio Playback MCP Server

Audio Playback MCP Server

Enables playback control of local audio files through a virtual audio output device, supporting play, stop, and status queries with configurable root directory and path safety enforcement.

Category
Visit Server

README

Audio Playback MCP Server

This repository provides an MCP server named audio-playback-server that exposes a single audio_playback tool. The tool lets an MCP client start, stop, and inspect playback of local audio files routed through a configurable virtual audio output device.

Features

  • Play audio files from a configurable root directory using ffplay.
  • Stop current playback.
  • Query current status with a position estimate.
  • Path safety enforcement to prevent leaving the configured root directory.

Configuration

The server reads configuration from environment variables and an optional JSON file. Environment variables take precedence over JSON values.

Required:

  • AUDIO_ROOT_DIR: Root directory containing allowed audio files.
  • AUDIO_OUTPUT_DEVICE: Identifier of the virtual output device.

Optional:

  • DEFAULT_FORMAT: File extension to append when none is provided (default wav).
  • FFPLAY_PATH: Path to the ffplay binary (default ffplay).
  • AUDIO_PLAYBACK_CONFIG: Path to a JSON config file containing any of the above keys.

An example config file is provided at config/audio_playback_config.example.json.

Installation

python -m venv .venv
source .venv/bin/activate
pip install -e .

Running the server (stdio)

AUDIO_ROOT_DIR=/path/to/audio \\
AUDIO_OUTPUT_DEVICE="Virtual Cable" \\
python -m audio_playback_server

The server listens on stdio following the MCP specification. Register the audio_playback tool with your MCP host using the tool schema defined in audio_playback_server/server.py.

Tool schema

The audio_playback tool accepts the following JSON input:

  • action: play, stop, or status (required)
  • filename: Relative path under AUDIO_ROOT_DIR (required for play)
  • loop: Loop playback until stopped (default false)
  • start_offset_ms: Start offset in milliseconds (default 0)

Responses always include success, message, and a state object with status, current_file, started_at_ms, and position_estimate_ms.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured