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 astronomer · MCP Server · ★ 445
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is agents safe to install? View the security audit →
agents AI agent tooling for data engineering workflows. Includes an MCP server for Airflow, a CLI tool () for interacting with Airflow from your terminal, and skills that extend AI coding agents with specialized capabilities for working with Airflow and data warehouses. Works with Claude Code, Cursor, and other agentic coding tools. Built by Astronomer. Apache 2.0 licensed and compatible with open-source Apache Airflow. Table of Contents Installation Quick Start Compatibility Claude Code Cursor Other MCP Clients Features MCP Server Skills Why Astro? User Journeys Airflow CLI () Configuration Warehouse Connections Airflow Usage Getting Started Development Local Development Setup [Adding Skills
| Stars | 445 |
| Forks | 63 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 73.2747613207271/100 |
| Open Issues | 22 |
| Last Updated | 2026-09-17 |
| Created | 2026-01-13 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~18k |
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agents is AI agent tooling for data engineering workflows.. It is categorized as a MCP Server with 445 GitHub stars.
agents is primarily written in Python. It covers topics such as agentic-workflow, agents, ai.
You can find installation instructions and usage details in the agents GitHub repository at github.com/astronomer/agents. The project has 445 stars and 63 forks, indicating an active community.
agents is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to agents on Agent Skills Hub include agnix, atlassian-mcp-server, concierge. 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: