WigAI

WigAI is an MCP server implemented as a Bitwig Studio extension. It exposes an HTTP-based MCP endpoint at http://localhost:61169/mcp that external AI agents can connect to in order to control Bitwig Studio through simple text-based commands. The server supports common MCP interactions such as transport control (start/stop playback), adjusting device parameters on selected devices, and launching clips or scenes. To use WigAI, ensure Bitwig Studio is installed and the WigAI extension is loaded and activated within Bitwig's Extensions preferences. Once active, connect your external AI agent to the MCP endpoint and begin issuing textual commands that WigAI will interpret and translate into Bitwig API actions.

Prerequisites:

• Bitwig Studio (5.2.7 or later)
• Java 21 LTS
• Gradle wrapper available in the project

Installation steps:

1. Clone the WigAI repository to your development machine.
2. Open a terminal in the repository root and build the extension: ./gradlew build
3. Locate the generated WigAI extension file (WigAI.bwextension) in build/extensions.
4. Copy WigAI.bwextension to Bitwig Studio's extensions directory:
   • On Windows: C:\Users<YourUser>\AppData\Roaming\Bitwig Studio\extensions
   • On macOS: /Users/<YourUser>/Library/Bitwig Studio/extensions
   • On Linux: ~/. Bitwig Studio/extensions
5. Launch Bitwig Studio, go to Preferences > Extensions, and enable WigAI.
6. WigAI will start and expose the MCP endpoint at http://localhost:61169/mcp once loaded.

Notes and tips:

• Ensure Bitwig Studio is running before starting WigAI.
• The MCP endpoint is hosted by the WigAI extension and Bindings may require network whitelisting if using a containerized environment.
• If you encounter connection issues, verify that Bitwig Studio is listening on the expected port (61169 by default) and that the WigAI extension is active in the Extensions list.
• WigAI relies on the Model Context Protocol; ensure your external AI agent supports MCP commands and adheres to the protocol for command structure and responses.
• This project uses the BMAD v2 method for AI agent integration and includes folders agents, ai, and docs used during development.