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 dadbodgeoff · MCP Server · ★ 785
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is drift safe to install? View the security audit →
Drift Codebase intelligence for AI. Detects patterns & conventions + remembers decisions across sessions. MCP server for any IDE. Offline CLI. Repository structure drift v1 depreciated/ – Legacy TypeScript implementation (deprecated) drift v2/ – Current Rust/TypeScript monorepo (active development) For v2 setup and usage, see or the docs in .
| Stars | 785 |
| Forks | 61 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 43.6664793503217/100 |
| Open Issues | 3 |
| Last Updated | 2026-08-20 |
| Created | 2026-01-19 |
| Platforms | cli, mcp, node, vscode |
| Est. Tokens | ~14k |
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drift is Codebase intelligence for AI. Detects patterns & conventions + remembers decisions across sessions. MCP server for any IDE. Offline CLI.. It is categorized as a MCP Server with 785 GitHub stars.
drift is primarily written in TypeScript. It covers topics such as ai-tools, cli, code-quality.
You can find installation instructions and usage details in the drift GitHub repository at github.com/dadbodgeoff/drift. The project has 785 stars and 61 forks, indicating an active community.
drift is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to drift on Agent Skills Hub include roam-code, mcp-fusion, claude-historian-mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
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: