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raye-deng/open-code-review

by Various

🤖 AI code quality gate for AI-generated code. Detects hallucinated packages, phantom dependencies, stale APIs, and more. MCP Server + CLI + CI/CD Action.

R

MCP

raye-deng/open-code-review

Added 1 June 2026

#ai #ai-generated-code #ci-cd #code-quality #code-review #developer-tools #github-actions #golang

Overview

Open Code Review is an AI code quality gate that scans AI-generated code for hallucinated packages, phantom dependencies, and stale APIs. It operates as an MCP server, CLI tool, and CI/CD action, all written in TypeScript.

Best for

Best for
Developers reviewing AI-generated code for dependency and API hallucinations

Use cases

  • Catch hallucinated imports and fake packages in AI-generated code
  • Verify dependency integrity before merging pull requests
  • Automate code review in CI/CD pipelines

How to use

Install

npx @opencodereview/mcp-server

Tools exposed

  • ocr_scan
  • ocr_heal
  • ocr_explain

Tested with

Claude Desktop, Cursor, Windsurf, VS Code Copilot

Example client config

{\n  "mcpServers": {\n    "open-code-review": {\n      "command": "npx",\n      "args": ["-y", "@opencodereview/mcp-server"]\n    }\n  }\n}

Notes

Open Code Review is an AI code quality gate that scans AI-generated code for hallucinated packages, phantom dependencies, and stale APIs. It operates as an MCP server, CLI tool, and CI/CD action, all written in TypeScript.

24 stars on GitHub. Last updated 2026-04-16.

Use cases

  • Catch hallucinated imports and fake packages in AI-generated code
  • Verify dependency integrity before merging pull requests
  • Automate code review in CI/CD pipelines

Pros

  • Targets specific AI-code pitfalls like phantom dependencies
  • Flexible deployment as CLI, server, or CI action
  • Lightweight TypeScript codebase

Cons

  • Small community with only 24 stars
  • Limited to detecting package and API issues, not broader code quality
  • Requires integration setup for each pipeline

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Targets specific AI-code pitfalls like phantom dependencies
  • Flexible deployment as CLI, server, or CI action
  • Lightweight TypeScript codebase

Cons

  • Small community with only 24 stars
  • Limited to detecting package and API issues, not broader code quality
  • Requires integration setup for each pipeline
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