Maintainer of this skill?
Automated security scan — not a certification.
by vstorm-co
Open-source AI teammates for your company. The self-hosted agent layer: build, run and govern AI agents on your own servers, models and rules. RAG, skills, a real browser, 4,700+ MCP servers and an API, with budgets, approvals and an audit trail. Apache-2.0, built on Pydantic AI.
# Add to your Claude Code skills
git clone https://github.com/vstorm-co/agenticosLast scanned: 10/17/2026
{
"issues": [
{
"file": ".claude/skills/mcp-connections/SKILL.md",
"line": 126,
"type": "secret-exfiltration",
"message": "Instruction appears to send credentials/secrets to an external endpoint",
"severity": "medium"
}
],
"status": "PASSED",
"scannedAt": "2026-10-17T08:19:29.731Z",
"npmAuditRan": true,
"pipAuditRan": true,
"promptInjectionRan": true
}See how agenticos compares with popular alternatives.
agenticos is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by vstorm-co. Open-source AI teammates for your company. The self-hosted agent layer: build, run and govern AI agents on your own servers, models and rules. RAG, skills, a real browser, 4,700+ MCP servers and an API, with budgets, approvals and an audit trail. Apache-2.0, built on Pydantic AI. It has 106 GitHub stars.
Yes. agenticos passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/vstorm-co/agenticos" and add it to your Claude Code skills directory (see the Installation section above).
agenticos is primarily written in Python. It is open-source under vstorm-co on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh agenticos against similar tools.
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⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
Automated security scan — not a certification.
AgenticOS gives every team AI teammates: agents that work with files, run code, browse the web and use your company's tools and knowledge. It is open source (Apache-2.0) and self-hosted, a layer you run on your own infrastructure. Build and publish agents in the browser, share them with colleagues, and manage their access, cost and results in one place.
New here? Click through the 14-slide introduction: the problem, the idea, the product on real screens, its controls and limits, and how to start. For every screen in detail, open the 44-slide product tour. Arrow keys step through either deck; O lists every slide.
Open the console to what your agents did, the calls waiting on you and the conversations to pick up again - with a tour of what they can do that is easy to miss.
A lead agent hands parts of a task to colleagues and writes up what they found - you see who it asked, and what each said.
Watch it click through sites, take over when a sign-in needs you, point at a spot to comment.
Switch tools on from illustrated cards, then give the draft a real job in the test chat beside them - here it charts a quarter's revenue against costs and reads the margin, before anyone else sees the agent.
An agent publishes a dashboard or a report as a page with a stable link and versions.
Connect Notion, GitHub, Jira or your own server, and choose which tools each agent may call.
AgenticOS is an MCP server. Add it with one command and sign in through the browser: your coding assistant can list and run agents, read runs and what they cost, and search and fill knowledge bases, within what you allowed.
AgenticOS is an open-source (Apache-2.0), self-hosted layer for building, sharing and governing AI agents across a company. Teams configure an agent in the browser by writing its instructions, choosing a model and switching on tools. They connect it to company documents and apps, and publish it to web chat, Slack, Mattermost, Telegram, a website widget or an API. Administrators control who can use each agent, what it may spend and which actions need a person's approval. Every run is recorded.
Most agent frameworks give you a library, so every change to an agent's behaviour is a pull request, a review and a release. That is the wrong shape for the small agents a company actually wants, because the person who knows what the agent should say is not the person with commit access. Code defines, configuration composes: engineers extend what there is to assemble, and configuration can only ever reach what code registered.
It runs on your own infrastructure with Docker Compose and works with 27 model providers, including local models through Ollama and vLLM. Agents run on Pydantic AI and pydantic-ai-harness; the layer around them uses FastAPI, PostgreSQL with pgvector and Next.js. It is maintained by Vstorm.
Who it is for:
How AgenticOS fits into a company: departments such as finance, operations or the board use shared agents in web chat, Slack or a private workspace. Your systems call agents through the API, and events or schedules start them automatically. Every request passes the same controls: roles, budgets, approvals, guardrails and a recorded run. Your data, vectors, code sandboxes, the credential vault and optional local models stay on your infrastructure. Hosted models,