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 ruvnet · MCP Server · ★ 595
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is metaharness safe to install? View the security audit →
MetaHarness Mint a custom AI agent harness from any repo. · open the Studio → (Repo: · CLI: · Library: ) What this is Every serious repo deserves its own agent. A repo-aware CLI, a repo-aware coding agent, a local MCP server, memory scoped to the project, skills generated from the actual file layout, governance policy, release verification, witness-signed provenance. mints those, on demand, from a GitHub URL or a blank slate. It is not another agent framework. It is a factory for agent
| Stars | 595 |
| Forks | 72 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 65.3474134312773/100 |
| Open Issues | 38 |
| Last Updated | 2026-08-18 |
| Created | 2026-06-13 |
| Platforms | claude-code, cli, codex, mcp, node |
| Est. Tokens | ~20k |
These tools work well together with metaharness for enhanced workflows:
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metaharness is 🛠️ The meta-harness for AI agents — scaffold your own focused, branded agent harness with its own npx CLI, MCP server, memory, learning loop, and witness-signed releases. Works with Claude Code, Code. It is categorized as a MCP Server with 595 GitHub stars.
metaharness is primarily written in TypeScript. It covers topics such as agent-harness, agent-harness-generator, agent-scaffolding.
You can find installation instructions and usage details in the metaharness GitHub repository at github.com/ruvnet/metaharness. The project has 595 stars and 72 forks, indicating an active community.
metaharness is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to metaharness on Agent Skills Hub include turbo-flow, commonly, memorix. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.