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 vstorm-co · MCP Server · ★ 61
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is subagents-pydantic-ai safe to install? View the security audit →
Subagents for Pydantic AI Multi-Agent Orchestration for Pydantic AI Nested Subagents — subagents spawn their own subagents • Runtime Agent Creation — create specialists on-the-fly • Auto-Mode Selection — intelligent sync/async decision Subagents for Pydantic AI adds multi-agent delegation to any Pydantic AI agent. Spawn specialized subagents that run synchro
| Stars | 61 |
| Forks | 19 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 72.6138016586258/100 |
| Open Issues | 7 |
| Last Updated | 2026-09-15 |
| Created | 2026-01-19 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~16k |
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subagents-pydantic-ai is Subagent Delegation framework for Pydantic AI, enabling nested subagents that can spawn their own specialists on-the-fly, with smart sync/async/auto mode selection, runtime agent creation, and clean m. It is categorized as a MCP Server with 61 GitHub stars.
subagents-pydantic-ai is primarily written in Python. It covers topics such as ai-agent-framework, aiagentsframework, anthropic.
You can find installation instructions and usage details in the subagents-pydantic-ai GitHub repository at github.com/vstorm-co/subagents-pydantic-ai. The project has 61 stars and 19 forks, indicating an active community.
subagents-pydantic-ai is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to subagents-pydantic-ai on Agent Skills Hub include mcp-server, mcp-fusion, c4-genai-suite. 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: