# Reaper

> Use this tool when you need to integrate AI assistants with Reaper digital audio workstation projects, solving problems like audio production assistance and project organization. It takes Reaper project files as input and outputs structured data on track layouts, plugin chains, and automation, making it accessible for AI models to analyze. This tool is ideal for use cases where AI-driven systems need to interact with music production workflows without requiring deep knowledge of the underlying file format.

Canonical page: https://skillsregistry.net/skills/dschuler36-reaper-project-analyzer  
JSON: https://api.skillsregistry.net/v1/skills/dschuler36-reaper-project-analyzer

## Description

This Reaper MCP server, developed for integration with Claude Desktop, provides a bridge between AI assistants and Reaper digital audio workstation projects. Built with Python and leveraging the MCP protocol, it offers tools for finding and parsing Reaper project files. The implementation focuses on extracting structured data from complex audio projects, making it accessible for AI models to analyze track layouts, plugin chains, automation, and other project elements. It's particularly useful for tasks like audio production assistance, project organization, or integrating music production workflows into AI-driven systems, enabling assistants to interact with Reaper projects without requiring deep knowledge of the underlying file format.

## Trust

- **Trust score (0–1):** 0.77
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/dschuler36-reaper-project-analyzer)
- **Repository:** <https://github.com/dschuler36/reaper-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "dschuler36-reaper-project-analyzer"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/dschuler36-reaper-project-analyzer` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/dschuler36-reaper-project-analyzer/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt