developer-tools

SlopWatch

joodascode

by joodascode

Track coding accuracy with SlopWatch, an automated reconciliation software for verifying code changes and managing accou

Tracks implementation claims versus actual delivery by monitoring file content changes, verifying code modifications through content analysis, and generating accountability workflows to measure coding accuracy in development environments.

github stars

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Real-time AI lie detectionSingle-call claim verificationCursor IDE compatible

best for

  • / Developers using AI pair programming tools
  • / Teams tracking AI coding accuracy
  • / Code review processes involving AI assistance

capabilities

  • / Register implementation claims and verify against actual file changes
  • / Track slop scores showing AI accuracy statistics
  • / Generate accountability rules for AI development workflows
  • / Monitor file content changes for verification
  • / Analyze code modifications through content comparison

what it does

Monitors AI coding claims by tracking what AI says it implemented versus what actually gets changed in your code files. Provides accountability scoring to catch AI lies about code modifications.

about

SlopWatch is a community-built MCP server published by joodascode that provides AI assistants with tools and capabilities via the Model Context Protocol. Track coding accuracy with SlopWatch, an automated reconciliation software for verifying code changes and managing accou It is categorized under developer tools. This server exposes 3 tools that AI clients can invoke during conversations and coding sessions.

how to install

You can install SlopWatch in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

SlopWatch is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

🎯 SlopWatch - AI Accountability MCP Server

Stop AI from lying about what it implemented! Track what AI claims vs what it actually does.

NPM Version NPM Downloads NPM Downloads Weekly Available on Smithery.ai Cursor MCP License: MIT

🚀 What's New in v2.7.0

Ultra-Minimal Responses - 90% less verbose output
🔄 Combined Tool - Single call instead of 2 separate tools
Seamless Workflow - Perfect for AI pair programming
🎯 Cursor MCP Compatible - Works seamlessly with Cursor IDE

🤔 Why SlopWatch?

Ever had AI say "I've added error handling to your function" but it actually didn't? Or claim it "implemented user authentication" when it just added a comment?

SlopWatch catches AI lies in real-time.

⚡ Quick Start

🎯 Option 1: Smithery (Easiest - 1 click install)

  1. Visit smithery.ai/server/@JoodasCode/slopwatch
  2. Click "Install to Cursor" or "Install to Claude"
  3. Done! ✨

Smithery handles hosting, authentication, and updates automatically

🔧 Option 2: NPM Direct (Manual Setup)

For Cursor IDE:

{
  "mcpServers": {
    "slopwatch": {
      "command": "npx",
      "args": ["slopwatch-mcp-server"]
    }
  }
}

Manual Cursor Setup:

  1. Open Cursor Settings (Cmd+Shift+J on Mac, Ctrl+Shift+J on Windows)
  2. Go to Features → Model Context Protocol
  3. Click "Add New MCP Server"
  4. Configure:
    • Name: SlopWatch
    • Type: stdio
    • Command: npx slopwatch-mcp-server

For Claude Desktop: Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "slopwatch": {
      "command": "npx",
      "args": ["slopwatch-mcp-server"]
    }
  }
}

Global NPM Install:

npm install -g slopwatch-mcp-server

🎮 How to Use

Method 1: Combined Tool (Recommended ⭐)

Perfect for when AI implements something and you want to verify it:

// AI implements code, then verifies in ONE call:
slopwatch_claim_and_verify({
  claim: "Add input validation to calculateSum function",
  originalFileContents: {
    "utils/math.js": "function calculateSum(a, b) { return a + b; }"
  },
  updatedFileContents: {
    "utils/math.js": "function calculateSum(a, b) {
  if (typeof a !== 'number' || typeof b !== 'number') {
    throw new Error('Invalid input');
  }
  return a + b;
}"
  }
});

// Response: "✅ PASSED (87%)"

Method 2: Traditional 2-Step Process

For when you want to claim before implementing:

// Step 1: Register claim
slopwatch_claim({
  claim: "Add error handling to user login",
  fileContents: {
    "auth.js": "function login(user) { return authenticate(user); }"
  }
});
// Response: "Claim ID: abc123"

// Step 2: Verify after implementation
slopwatch_verify({
  claimId: "abc123",
  updatedFileContents: {
    "auth.js": "function login(user) {
  try {
    return authenticate(user);
  } catch (error) {
    throw new Error('Login failed');
  }
}"
  }
});
// Response: "✅ PASSED (92%)"

🛠️ Available Tools

ToolDescriptionResponse
slopwatch_claim_and_verifyRecommended - Claim and verify in one call✅ PASSED (87%)
slopwatch_statusGet your accountability statsAccuracy: 95% (19/20)
slopwatch_setup_rulesGenerate .cursorrules for automatic enforcementMinimal rules content

🎯 Cursor IDE Integration

SlopWatch is designed specifically for Cursor IDE and AI pair programming:

Automatic Detection

  • Detects when AI claims to implement features
  • Automatically suggests verification
  • Integrates seamlessly with Cursor's Composer

Smart Workflow

1. AI: "I'll add error handling to your function"
2. SlopWatch: Automatically tracks the claim
3. AI: Implements the code
4. SlopWatch: Verifies implementation matches claim
5. Result: ✅ PASSED (92%) or ❌ FAILED (23%)

Perfect for:

  • Code reviews - Verify AI actually implemented what it claimed
  • Pair programming - Real-time accountability during development
  • Learning - Understand what AI actually does vs what it says
  • Quality assurance - Catch implementation gaps before they become bugs

💡 Real-World Examples

Example 1: API Endpoint Enhancement

// AI says: "I'll add rate limiting to your API endpoint"

slopwatch_claim_and_verify({
  claim: "Add rate limiting middleware to /api/users endpoint",
  originalFileContents: {
    "routes/users.js": "app.get('/api/users', (req, res) => { ... })"
  },
  updatedFileContents: {
    "routes/users.js": "const rateLimit = require('express-rate-limit');
const limiter = rateLimit({ windowMs: 15*60*1000, max: 100 });
app.get('/api/users', limiter, (req, res) => { ... })"
  }
});
// Result: ✅ PASSED (94%)

Example 2: React Component Update

// AI claims: "Added responsive design with CSS Grid"

slopwatch_claim_and_verify({
  claim: "Make UserCard component responsive using CSS Grid",
  originalFileContents: {
    "components/UserCard.jsx": "const UserCard = () => <div className="user-card">...</div>"
  },
  updatedFileContents: {
    "components/UserCard.jsx": "const UserCard = () => <div className="user-card grid-responsive">...</div>",
    "styles/UserCard.css": ".grid-responsive { display: grid; grid-template-columns: repeat(auto-fit, minmax(300px, 1fr)); gap: 1rem; }"
  }
});
// Result: ✅ PASSED (89%)

📊 Accountability Stats

Track your AI's honesty over time:

slopwatch_status();
// Returns: "Accuracy: 95% (19/20)"
  • Accuracy Score: Percentage of claims that were actually implemented
  • Claim Count: Total number of implementation claims tracked
  • Success Rate: How often AI delivers what it promises

🔧 Advanced Configuration

Auto-Enforcement with .cursorrules

Generate automatic accountability rules:

slopwatch_setup_rules();

This creates a .cursorrules file that automatically enforces SlopWatch verification for all AI implementations.

Custom Verification

SlopWatch analyzes:

  • File changes - Did the files actually get modified?
  • Code content - Does the new code match the claim?
  • Implementation patterns - Are the right patterns/libraries used?
  • Keyword matching - Does the code contain relevant keywords?

🚀 Why Choose SlopWatch?

For Developers:

  • Catch AI lies before they become bugs
  • Learn faster by seeing what AI actually does
  • Improve code quality through automatic verification
  • Save time with streamlined accountability

For Teams:

  • Standardize AI interactions across team members
  • Track AI reliability over time
  • Reduce debugging from AI implementation gaps
  • Build trust in AI-assisted development

For Cursor Users:

  • Native integration with Cursor's Composer
  • Seamless workflow - no context switching
  • Real-time feedback during development
  • Ultra-minimal responses - no verbose output

🎯 Getting Started with Cursor

  1. Install SlopWatch using one of the methods above
  2. Open Cursor and start a new chat with Composer
  3. Ask AI to implement something: "Add input validation to my function"
  4. Watch SlopWatch work: It automatically tracks and verifies the claim
  5. Get instant feedback: ✅ PASSED (87%) or ❌ FAILED (23%)

🔍 Troubleshooting

Common Issues:

  • Tools not showing: Restart Cursor after installation
  • Verification failed: Check if files were actually modified
  • NPM errors: Try npm cache clean --force and reinstall

Debug Mode:

Enable detailed logging by setting DEBUG=true in your environment.

📈 Roadmap

  • Visual dashboard for accountability metrics
  • Integration with Git for commit verification
  • Team analytics for multi-developer projects
  • Custom verification rules for specific frameworks
  • IDE extensions for other editors

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

📝 License

MIT License - see LICENSE for details.

🌟 Support


Made with ❤️ for the Cursor community

Stop AI from lying about what it implemented. Start using SlopWatch today!

FAQ

What is the SlopWatch MCP server?
SlopWatch is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for SlopWatch?
This profile displays 65 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.4 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.465 reviews
  • Isabella Liu· Dec 28, 2024

    SlopWatch is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Li Bansal· Dec 16, 2024

    According to our notes, SlopWatch benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Emma Martinez· Dec 16, 2024

    We wired SlopWatch into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Olivia White· Dec 12, 2024

    We wired SlopWatch into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Isabella Garcia· Nov 19, 2024

    We wired SlopWatch into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Isabella Zhang· Nov 7, 2024

    SlopWatch is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Emma Singh· Nov 7, 2024

    SlopWatch is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Anaya Robinson· Nov 3, 2024

    SlopWatch is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Lucas Huang· Oct 26, 2024

    SlopWatch is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Amina Martinez· Oct 26, 2024

    SlopWatch is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

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