agenite: Build powerful AI agents with TypeScript

by subeshb1 · MCP Server · ★ 68

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

How to install agenite

npm install @agenite/agent @agenite/tool @agenite/llm
npm install @agenite/openai

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 70/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

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Quick Facts

Stars68
Forks9
LanguageMDX
CategoryMCP Server
LicenseMIT
Quality Score70/100
Open Issues3
Last Updated2025-09-13
Created2025-01-26
Platformsaws, cli, mcp
Est. Tokens~287k

About agenite

🤖 Agenite A modern, modular, and type-safe framework for building AI agents using typescript What is Agenite? Agenite is a powerful TypeScript framework designed for building sophisticated AI agents. It provides a modular, type-safe, and flexible architecture that makes it easy to create, compose, and control AI agents with advanced capabilities.

agenite alternative? Top 6 similar tools

Looking for a agenite alternative? If you're comparing agenite with other mcp server 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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    [archived] c4 GenAI Suite

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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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