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 ArihantDeva · MCP Server · ★ 121
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is heimdall safe to install? View the security audit →
Heimdall Your agent keeps rebuilding work you already did. Heimdall makes it stop. Heimdall gives AI coding agents persistent memory across every repository and project you work on so the question "did I already solve this in another project?" gets answered by one verified search instead of twenty minutes of grep, , and loops. The problem it solves 1. Memory that doesn't live in one repository. Every other memory tool is per-project. But your work isn't: the optimized functions you built in one project could be useful somewhere else. Heimdall indexes everything you touch into one semantic graph, so kno
| Stars | 121 |
| Forks | 9 |
| Language | JavaScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 65.0495337816984/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-19 |
| Created | 2026-08-20 |
| Platforms | claude-code, cli, mcp, node |
| Est. Tokens | ~22k |
These tools work well together with heimdall for enhanced workflows:
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heimdall is A lightweight CPU only memory approach with ranked retrieval. Simple, yet effective.. It is categorized as a MCP Server with 121 GitHub stars.
heimdall is primarily written in JavaScript. It covers topics such as ai-agents, claude-code, cli.
You can find installation instructions and usage details in the heimdall GitHub repository at github.com/ArihantDeva/heimdall. The project has 121 stars and 9 forks, indicating an active community.
heimdall is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to heimdall on Agent Skills Hub include octocode, gno, roam-code. 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: