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 Nya-Foundation · LLM Plugin · ★ 976
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is NyaProxy safe to install? View the security audit →
NyaProxy A lightweight, header-based API proxy for managing authenticated upstream services. English 日本語 Centralize credential injection, quota-aware routing, rate limiting, retries, and observability for any HTTP API that uses keys or tokens. <img src="https://codecov.io/gh/Nya-Foundation/nyaproxy/branch/main/graph/badge.svg" alt="Code Cove
| Stars | 976 |
| Forks | 16 |
| Language | Python |
| Category | LLM Plugin |
| License | MIT |
| Quality Score | 75.8676209729725/100 |
| Last Updated | 2026-07-20 |
| Created | 2025-04-13 |
| Platforms | browser, gemini, python |
| Est. Tokens | ~16k |
These tools work well together with NyaProxy for enhanced workflows:
Looking for a NyaProxy alternative? If you're comparing NyaProxy with other llm plugin tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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NyaProxy is NyaProxy acts like a smart, central manager for accessing various online services (APIs) – think AI tools (like OpenAI, Gemini, Anthropic), image generators, or almost any web service that uses access. It is categorized as a LLM Plugin with 976 GitHub stars.
NyaProxy is primarily written in Python. It covers topics such as api-management, api-monitoring, developer-tools.
You can find installation instructions and usage details in the NyaProxy GitHub repository at github.com/Nya-Foundation/NyaProxy. The project has 976 stars and 16 forks, indicating an active community.
NyaProxy is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to NyaProxy on Agent Skills Hub include mirascope, mcp-nixos, api200. 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: