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 Mathews-Tom · MCP Server · ★ 66
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is archex safe to install? View the security audit →
archex Verified local code context for agents. AI coding agents usually start by opening a file, following an import, checking a type definition, and backtracking through the repo until the context window is partly spent before the real task starts. archex does that retrieval and structural expansion up front and returns a ranked, token-budgeted context bundle plus a receipt that records what was included, what was skipped, and whether the bundle is complete enough to act on. It runs locally, uses deterministic retrieval and analysis, and does not require hosted inference or an API key. The v0.13 line adds stronger benchmark trust surfaces, bundle-only evaluator support, and default 4-bit TurboQuant vector storage for local vector indexes. Start: 30-second quickstart · MCP and Claude Code · Python API · Local metrics · Compatibility matrix · [Installation trust con
| Stars | 66 |
| Forks | 6 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 61.7327574412185/100 |
| Last Updated | 2026-10-04 |
| Created | 2026-02-27 |
| Platforms | mcp, python |
| Est. Tokens | ~19k |
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archex is Verified code context for agents. It is categorized as a MCP Server with 66 GitHub stars.
archex is primarily written in Python. It covers topics such as agents, archex, ast.
You can find installation instructions and usage details in the archex GitHub repository at github.com/Mathews-Tom/archex. The project has 66 stars and 6 forks, indicating an active community.
archex is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to archex on Agent Skills Hub include leantoken, srclight, codebase-context. 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: