by ArchieIndian · MCP Server · ★ 58
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
openclaw-superpowers 56 ready-to-use skills that make your AI agent autonomous, self-healing, and self-improving. A plug-and-play skill library for OpenClaw — the open-source AI agent runtime. Gives your agent structured thinking, security guardrails, persistent memory, cron scheduling, self-recovery, and the ability to write its own new skills during conversation. Built for developers who want their AI agent to run autonomously 24/7, not just respond to prompts in a chat window. Inspired by obra/superpowers. Extended for agents that never sleep. Why this exists Most AI agent frameworks give you a chatbot that forgets everything between sessions. OpenClaw is different — it runs persistently, handles multi-hour tasks, and has native cron scheduling. But out of the box, it doesn't know how to use those capabilities well. openclaw-superpowers bridges that gap. Install 56 skills in one command, and your agent immediately knows how to: Think befor
| Stars | 58 |
| Forks | 11 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 63.9134621942368/100 |
| Open Issues | 1 |
| Last Updated | 2026-05-03 |
| Created | 2026-03-14 |
| Platforms | mcp, python |
| Est. Tokens | ~44k |
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openclaw-superpowers is 44 plug-and-play skills for OpenClaw — self-modifying AI agent with cron scheduling, security guardrails, persistent memory, knowledge graphs, and MCP health monitoring. Your agent teaches itself new . It is categorized as a MCP Server with 58 GitHub stars.
openclaw-superpowers is primarily written in Python. It covers topics such as agent-framework, ai-agent, ai-automation.
You can find installation instructions and usage details in the openclaw-superpowers GitHub repository at github.com/ArchieIndian/openclaw-superpowers. The project has 58 stars and 11 forks, indicating an active community.
The top alternatives to openclaw-superpowers on Agent Skills Hub include deterministic-agent-control-protocol, rampart, omega-memory. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.