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 cyanheads · MCP Server · ★ 478
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is atlas-mcp-server safe to install? View the security audit →
ATLAS: Task Management System []() ATLAS (Adaptive Task & Logic Automation System) is a project, knowledge, and task management system for LLM Agents. Built on a 3-node architecture: ++
| Stars | 478 |
| Forks | 66 |
| Language | TypeScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 74.5612726698023/100 |
| Open Issues | 10 |
| Last Updated | 2025-07-22 |
| Created | 2024-12-16 |
| Platforms | mcp, node |
| Est. Tokens | ~225k |
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atlas-mcp-server is A Model Context Protocol (MCP) server for ATLAS, a Neo4j-powered task management system for LLM Agents - implementing a three-tier architecture (Projects, Tasks, Knowledge) to manage complex workflows. It is categorized as a MCP Server with 478 GitHub stars.
atlas-mcp-server is primarily written in TypeScript. It covers topics such as agents, ai, deep-research.
You can find installation instructions and usage details in the atlas-mcp-server GitHub repository at github.com/cyanheads/atlas-mcp-server. The project has 478 stars and 66 forks, indicating an active community.
atlas-mcp-server is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to atlas-mcp-server on Agent Skills Hub include py-gpt, npcpy, awesome-hacking-lists. 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: