esperanto — security grade SAFE, quality 68/100

Security audit verdict: SAFE · quality 68/100

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 lfnovo · Agent Tool · ★ 212

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is esperanto safe to install? View the security audit →

About esperanto

Esperanto 🌐 Esperanto is a powerful Python library that provides a unified interface for interacting with various Large Language Model (LLM) providers. It simplifies the process of working with different AI models (LLMs, Embedders, Transcribers, and TTS) APIs by offering a consistent interface while maintaining provider-specific optimizations. Why Esperanto? 🚀 🪶 Ultra-Lightweight Architecture Direct HTTP Communication: All providers communicate directly via HTTP APIs using - no bulky vendor SDKs required Minimal Dependencies: Unlike LangChain and similar frameworks, Esperanto has a tiny footprint with zero overhead layers Production-Ready Performance: Direct API calls mean faster response times and lower memory usage 🔄 True Provider Flexibility Standardized Responses: Switch between any provider (OpenAI ↔ Anthropic ↔ Google ↔ etc.) without changing a single line of code Consistent Interface: Same methods, same

anthropicembeddingsgeminilangchainlanguage-modelopenai

Quick Facts

Stars212
Forks49
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score67.6470045334137/100
Open Issues28
Last Updated2026-09-05
Created2024-11-23
Platformsgemini, python
Est. Tokens~21k

esperanto alternative? Top 6 similar tools

Looking for a esperanto alternative? If you're comparing esperanto with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • vllora by vllora · ⭐ 812

    Debug your AI agents

  • SimplerLLM by hassancs91 · ⭐ 219

    Python library for building with LLMs. One interface across 11 providers (OpenAI, Anthropic, Gemini, DeepSeek,

  • InferrLM by sbhjt-gr · ⭐ 100

    InferrLM - On-device AI for iOS & Android

  • SearChat by sear-chat · ⭐ 1.0k

    Search + Chat = SearChat(AI Chat with Search), Support OpenAI/Anthropic/VertexAI/Gemini, DeepResearch, SearXNG

  • gateway by adaline · ⭐ 605

    The only fully local production-grade Super SDK that provides a simple, unified, and powerful interface for ca

  • Notate by Hairetsu · ⭐ 259

    Notate is a desktop chat application that takes AI conversations to the next level. It combines the simplicity

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Frequently Asked Questions

What is esperanto?

esperanto is A unified interface for various AI model providers. It is categorized as a Agent Tool with 212 GitHub stars.

What programming language is esperanto written in?

esperanto is primarily written in Python. It covers topics such as anthropic, embeddings, gemini.

How do I install or use esperanto?

You can find installation instructions and usage details in the esperanto GitHub repository at github.com/lfnovo/esperanto. The project has 212 stars and 49 forks, indicating an active community.

What license does esperanto use?

esperanto is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to esperanto?

The top alternatives to esperanto on Agent Skills Hub include vllora, SimplerLLM, InferrLM. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

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:

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