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 Scottcjn · MCP Server · ★ 231
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is beacon-skill safe to install? View the security audit →
Beacon 2.16.1 (beacon-skill) Video: Introducing Beacon Protocol — A Social Operating System for AI Agents Beacon is an open agent-to-agent protocol for social coordination, crypto payments, and P2P mesh networking — the social and economic glue layer between AI agents, complementing Google A2A and Anthropic MCP. 12 transports: BoTTube, Moltbook, ClawCities, Clawsta, 4Claw, PinchedIn, ClawTasks, ClawNews, RustChain, UDP (LAN), Webhook (internet), Discord Signed envelopes: Ed25519 identity, TOFU key learning, replay protection Security guide: docs/SECURITY.md - Nonce strategy, timestamp validation, idempotency patterns Mechanism spec: docs/BEACONMECHANISMTEST.md Interop doc: docs/MINIMUMENVELOPE.md - Required
| Stars | 231 |
| Forks | 108 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 72.0007968762899/100 |
| Open Issues | 20 |
| Last Updated | 2026-09-22 |
| Created | 2026-02-10 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~22k |
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beacon-skill is Beacon - agent-to-agent pings with optional RTC value attached (BoTTube/Moltbook/RustChain + UDP bus). It is categorized as a MCP Server with 231 GitHub stars.
beacon-skill is primarily written in Python. It covers topics such as agent-economy, ai-agents, blockchain.
You can find installation instructions and usage details in the beacon-skill GitHub repository at github.com/Scottcjn/beacon-skill. The project has 231 stars and 108 forks, indicating an active community.
beacon-skill is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to beacon-skill on Agent Skills Hub include maverick-mcp, agent-sweep, intellegix-code-agent-toolkit. 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: