by CloudChef · Codex Skill · ★ 56
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
[!NOTE] This repository contains the AtlasClaw core implementation, including the agent runtime, API layer, channel adapters, provider registry, skills, tools, and session/memory management，see atlasclaw.ai. Concrete providers are not implemented in this repository. AtlasClaw loads provider packages from . In a sibling-repository layout, a common value is . AtlasClaw AtlasClaw is an enterprise agent framework that lets employees interact with multiple enterprise systems through one conversational AI interface. Instead of switching between separate consoles, dashboards, and approval portals, users can use natural language to trigger workflows, query operational data, and complete cross-system tasks from a single entry point. Background Enterprise software teams often need to work across CRM, ITSM, Monitoring, HR, Finance, OA and other internal systems. The challenge is not only system fragmentation, but also the mismatch between data models, workflow boundaries, authorization models, and user experience across those systems.
| Stars | 56 |
| Forks | 15 |
| Language | Python |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 70.3238948663227/100 |
| Last Updated | 2026-06-17 |
| Created | 2026-03-11 |
| Platforms | python |
| Est. Tokens | ~16k |
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atlasclaw is AtlasClaw is an enterprise agent framework supporting mutliple users and multi system integration.. It is categorized as a Codex Skill with 56 GitHub stars.
atlasclaw is primarily written in Python. It covers topics such as agent, agent-skills, agentic-ai.
You can find installation instructions and usage details in the atlasclaw GitHub repository at github.com/CloudChef/atlasclaw. The project has 56 stars and 15 forks, indicating an active community.
atlasclaw is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to atlasclaw on Agent Skills Hub include oreilly-ai-agents, agent-skills, latchkey. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.