by sandbaseai · MCP Server · ★ 642
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/sandbaseai/sandbase-harness.git
Taken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 642 |
| Forks | 78 |
| Language | TypeScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 75/100 |
| Open Issues | 1 |
| Last Updated | 2026-11-04 |
| Created | 2026-07-11 |
| Platforms | docker, k8s, mcp, node |
| Est. Tokens | ~16k |
managed-agents A local-first runtime for AI agents. Sessions, sandboxed tools, memory, credentials, audit trails, and a built-in Console — all running on your machine or in your own infrastructure. Why Agent SDKs handle the model loop.
These tools work well together with sandbase-harness for enhanced workflows:
Looking for a sandbase-harness alternative? If you're comparing sandbase-harness with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Supercharge AI Agents, Safely
Open-source agent runtime — SSH-native isolation, eBPF egress policy, Kubernetes + LXC backends, GPU passthrou
One place to manage & connect to all your MCP servers
Structural memory for AI coding agents. Bi-temporal graph, MCP-native, zero LLM calls. Cursor · Claude Code ·
Remote approvals, policy checks, and execution evidence for unattended AI agents.
MCP Aggregator, Orchestrator, Middleware, Gateway in one docker
Explore other popular mcp server tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: