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 aaronnat23 · MCP Server · ★ 98
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is disp8ch safe to install? View the security audit →
Chat in plain English. Get real workflows, real decisions, and shipped work.One app. Your machine. Your data. Website · Install · Why disp8ch · Screenshots · First Prompts · Run Fully Local · All Features · FAQ Most AI tools give you a chat box. disp8ch gives
| Stars | 98 |
| Forks | 2 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 48.6445355213528/100 |
| Last Updated | 2026-09-02 |
| Created | 2026-06-22 |
| Platforms | mcp, node |
| Est. Tokens | ~13k |
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disp8ch is Self-hosted AI workspace where chat becomes visual workflows, multi-agent operations, and reviewable automations. Local memory; local or cloud models. It is categorized as a MCP Server with 98 GitHub stars.
disp8ch is primarily written in TypeScript. It covers topics such as agentic-ai, ai-agents, automation.
You can find installation instructions and usage details in the disp8ch GitHub repository at github.com/aaronnat23/disp8ch. The project has 98 stars and 2 forks, indicating an active community.
disp8ch is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to disp8ch on Agent Skills Hub include ai-agent-automation, c4-genai-suite, captain-claw. 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: