The Cleanup Crew MCP Server

Introduction

The Cleanup Crew MCP server bridges the gap between AI coding assistants and human expertise. When AI tools like Cursor, GitHub Copilot, or Claude Code hit a wall on a complex problem, this server allows you to escalate the issue directly to a team of expert developers without leaving your IDE.

The server exposes a single, powerful tool—request_help—that captures comprehensive context about your current coding session and packages it for the support team. This includes your conversation history, workspace state, file diffs, diagnostics, dependencies, and environment details, all sent seamlessly through the Model Context Protocol.

Once a request is submitted, Cleanup Crew creates a private Discord channel and connects you with an expert developer within 15–60 minutes (depending on your subscription tier), offering real-time text and voice support until your issue is resolved. This makes it ideal for founders and developers who want human backup on-demand without hiring a full-time engineer.

Use Cases

1. Debugging runtime errors AI can't diagnose When your AI assistant repeatedly fails to fix a complex exception or stack trace, escalate the full error context to a human expert.

• Sample prompt: I've been stuck on this "Cannot read property 'map' of undefined" error in my React component for an hour and Claude keeps giving me fixes that don't work. Request help from the support team with my current error logs and the component file.

2. Multi-file architecture reasoning When an issue spans multiple files and the AI loses track of the broader codebase context, send the workspace structure for expert analysis.

• Sample prompt: My authentication flow is broken across three files—authMiddleware.js, session.js, and login.tsx—and the AI can't connect the dots. Send a help request including these files and my workspace structure.

3. Getting unblocked on architecture decisions When you need guidance on a technical implementation strategy rather than just code, request expert advisory input.

• Sample prompt: I can't decide whether to use WebSockets or Server-Sent Events for my real-time notifications feature. Request help and include my current backend setup and dependencies so an expert can advise.

4. Late-night launch blockers When you're on a deadline and AI tools aren't cutting it, escalate immediately with full session context.

• Sample prompt: We're launching tomorrow and the payment integration keeps throwing a 400 error. Please request urgent help and include my conversation history, the Stripe integration files, and recent git diffs.

5. Resolving issues after multiple failed AI attempts When you've tried several AI-suggested fixes that didn't work, share those attempts so experts don't repeat them.

• Sample prompt: I've tried three different fixes for this CORS issue and none worked. Request help and include the solutions I already attempted along with their resulting errors so the expert has full context.

6. Performance troubleshooting When your app is slow and AI can't pinpoint the bottleneck, send performance metrics for human review.

• Sample prompt: My Node.js API endpoint is taking 8 seconds to respond and I can't figure out why. Request help and include CPU usage, memory metrics, and the relevant route handler file.

7. Non-technical founder support When you lack the technical depth to interpret AI output, hand off to an expert for a real conversation.

• Sample prompt: I'm not a developer and Cursor's suggestions are confusing me on this database migration. Request help from the Cleanup Crew team and include my project files and the migration script.

Note: When triggering the request_help tool, avoid sending sensitive data such as API keys, credentials, or personal information in your context.