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 Swival · MCP Server · ★ 341
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is swival safe to install? View the security audit →
Swival A coding agent for any model. Documentation Swival is a CLI coding agent built to be practical, reliable, and easy to use. It works with frontier models, but its main goal is to be as reliable as possible with smaller models, including local ones. It is designed from the ground up to handle tight context windows and limited resources without falling apart. It connects to LM Studio, llama.cpp, HuggingFace Inference API, OpenRouter, Google Gemini, Gemini Enterprise Agent Platform (formerly Vertex AI), ChatGPT Plus/Pro, AWS Bedrock, any OpenAI-compatible server (ollama, mlxlm.server, vLLM, etc.), or any external command (, custom wrappers, etc.), sends your task, and runs an autonomous tool loop until it produces an answer. With LM Studio and llama.cpp it auto-discovers your loaded model, so there's nothing to configure. Pure Python, no framework. Quickstart Pick the provider that matches how you want to run models: First command
| Stars | 341 |
| Forks | 21 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 63.2964421232415/100 |
| Last Updated | 2026-09-22 |
| Created | 2026-02-24 |
| Platforms | cli, mcp, python |
| Est. Tokens | ~17k |
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swival is A small, powerful, open-source CLI coding agent that works with open models.. It is categorized as a MCP Server with 341 GitHub stars.
swival is primarily written in Python. It covers topics such as a2a, agent, agent-to-agent.
You can find installation instructions and usage details in the swival GitHub repository at github.com/Swival/swival. The project has 341 stars and 21 forks, indicating an active community.
swival is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to swival on Agent Skills Hub include blade-code, adal-cli, agnix. 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: