No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by johnhuang316 · MCP Server · ★ 996
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is code-index-mcp safe to install? View the security audit →
Code Index MCP Intelligent code indexing and analysis for Large Language Models Transform how AI understands your codebase with advanced search, analysis, and navigation capabilities. Overview Code Index MCP is a Model Context Protocol server that bridges the gap between AI models and complex codebases. It provides intelligent indexing, advanced search capabilities, and detailed code analysis to help AI assistants understand and navigate your projects effectively. Perfect for: Code review, refactoring, documentation generation, debugging assistance, and architectural analysis. Quick Start 🚀 Recommended Setup (Most Users) The easiest way to get started with any MCP-compatible application: Prerequisites: Python 3.10+ and uv Add to your MCP configuration (e.g., claudedes
| Stars | 996 |
| Forks | 122 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 68.8717262422221/100 |
| Open Issues | 21 |
| Last Updated | 2026-07-27 |
| Created | 2025-03-18 |
| Platforms | mcp, python |
| Est. Tokens | ~17k |
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code-index-mcp is A Model Context Protocol (MCP) server that helps large language models index, search, and analyze code repositories with minimal setup. It is categorized as a MCP Server with 996 GitHub stars.
code-index-mcp is primarily written in Python.
You can find installation instructions and usage details in the code-index-mcp GitHub repository at github.com/johnhuang316/code-index-mcp. The project has 996 stars and 122 forks, indicating an active community.
code-index-mcp is released under the MIT license, making it free to use and modify according to the license terms.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: