Code Reaper
CodeReaper is an AI-driven MCP tool for Cursor that finds and removes dead JavaScript by exploring real UIs and capturing V8 coverage
CodeReaper
CodeReaper is an AI-driven MCP tool for Cursor that finds and removes dead JavaScript by exploring real UIs and capturing V8 coverage.
Key Features
- Autonomous UI exploration via the Index browser agent
- V8 precise coverage to identify zero-execution functions
- Risk scoring and removal recommendations
- Patch generation and optional verification replay
- MCP integration for Cursor workflows
Quick Install
pip install codereaper
playwright install chromium
codereaper
When you first run codereaper, it prompts for your Gemini API key and saves it in your global ~/.cursor/mcp.json so Cursor can invoke it later.
Alternative Install
# pipx
pipx run codereaper
Prerequisites
- Python 3.11+
- Playwright Chromium (installed via
playwright install chromium) - A Gemini API key (or OpenAI / Anthropic if you change providers)
Quick Start
- Install and run
codereaper(it updates~/.cursor/mcp.json) - Restart Cursor
- Ask the assistant:
"Find dead JavaScript code on http://localhost:3000"
Usage
Command:
codereaper
Example scan with local source mapping:
"Find dead code on http://localhost:3000, source is in ./test_site"
MCP Tools
| Tool | Description |
|---|---|
find_dead_code | Full pipeline: scan + analyze. Returns dead-code report with file paths, line numbers, risk scores, and removal recommendations. |
scan_website | Scan only (no analysis). Returns scan_id for later use. |
analyze_dead_code | Analyze a completed scan. Takes scan_id. |
generate_patches | Generate unified diffs to remove dead code (conservative / balanced / aggressive). |
get_patch_diff | Retrieve the combined diff for a patch. |
apply_patch | Apply a patch to source files (stores snapshots for rollback). |
verify_patch | Re-run the browser agent to check for regressions after patching. |
rollback_patch | Restore original files from pre-patch snapshots. |
list_scans | List recent scans. |
get_scan_status | Get detailed status of a scan. |
Troubleshooting
- If the browser doesn’t open, install Chromium:
playwright install chromium - If the scan fails with key errors, ensure
GEMINI_API_KEYexists in~/.cursor/mcp.json - If local pages don’t load, confirm your dev server is running and reachable
- If Gemini rate limits hit, retry after the quota window resets
Update
- 02-09-2026: v0.2.3 release
Issues & Feedback
Open an issue with steps to reproduce and logs if possible. Feedback and suggestions are welcome.
Verwandte Server
Scout Monitoring MCP
SponsorPut performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
SponsorAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
Dify Server
Integrates the Dify AI API to generate Ant Design business component code. Supports text, image inputs, and streaming responses.
SSE MCP Server Example
An example MCP Server demonstrating Server-Sent Events (SSE) usage.
AgentExecMCP
A secure, Docker-based server providing core execution capabilities for AI agents.
GhostQA
GhostQA sends AI personas through your application — they look at the screen, decide what to do, and interact like real humans. No test scripts. No selectors. You describe personas and journeys in YAML, and GhostQA handles the rest.
MCP Remote Machine Control
Provides remote machine control capabilities, eliminating SSH overhead for token-efficient system operations.
Moralis Web3 API
Interact with the Moralis Web3 API to access blockchain data across multiple networks through a structured interface.
Forge
GPU kernel optimization - 32 swarm agents turn PyTorch into fast CUDA/Triton kernels on real datacenter GPUs with up to 14x speedup
Helm MCP
MCP server to work with Helm charts
BlenderMCP
Connects Blender to AI models via MCP for prompt-assisted 3D modeling, scene creation, and manipulation.
Text2Sim MCP Server
A multi-paradigm simulation engine for Discrete-Event and System Dynamics, enabling natural language-based simulations via MCP.