AI-Gateway logo
AI-Gateway
★ 1.0k
vs
nanobot logo
nanobot
★ 49.3k

AI-Gateway vs nanobot

AI-Gateway: AI Gateway is an enterprise-grade gateway powered by Azure API Management for managing AI models, tools, and agents. It provides security, performance, observability, cost control, and extensibility. The project includes 30+ hands-on labs to help users deploy and manage AI gateway capabilities in Azure.; nanobot: nanobot is an ultra-lightweight, self-hosted personal AI agent framework built in Python, offering a readable core for multi-agent delegation and automation. It supports various interfaces including WebUI, terminal, and chat apps, integrating tools, long-term memory, and OpenAI-compatible APIs.

01

TL;DR

AI-Gateway logo
AI-GatewayMulti-Agent · ★ 1.0k

Manage and control access to Large Language Models with enterprise-grade policies

nanobot logo
nanobotMulti-Agent · ★ 49.3k
When to choose:
  • You want a lightweight, hackable Python personal AI agent framework with clean code, a WebUI, and built-in MCP client support.
  • You prefer an easy-to-read, self-hosted agent core without the enterprise boilerplate of heavy agent frameworks.
When to skip:
  • You require production-grade distributed state checkpointing, strict Pydantic type validation, or multi-role team SOPs; Pydantic AI or CrewAI offer more mature infrastructure.
  • Your production stack is .NET or Go; Microsoft Agent Framework covers those runtimes.
02

Side-by-Side Comparison

Field
AI-Gateway logoAI-Gateway
nanobot logonanobot
Category
Multi-Agent
Multi-Agent
Stars
★ 1.0k
★ 49.3k
License
MIT
MIT
Install Command
git clone https://github.com/Azure-Samples/AI-Gateway.git && cd AI-Gateway && code .
curl -fsSL https://raw.githubusercontent.com/HKUDS/nanobot/main/scripts/install.sh | sh
Updated
1mo ago
1d ago
Open Source
Yes
Yes
Tags
a2a, agents, apimanagement
AI Agent Framework, Self-hosted, Python
03

Features

AI-Gateway logoAI-Gateway
01Security with OAuth 2.0, managed identities, and content safety filtering
02Performance with load balancing, semantic caching, and request routing
03Observability with token metrics, built-in logging, and tracing
04Cost control with rate limiting, quota management, and FinOps framework
05Extensibility with MCP protocol support, function calling, and multi-model routing
nanobot logonanobot
01Persistent workflows: goals, memory, tools, and chat context survive long-running work.
02Chat-native reach: WebUI, API, Telegram, Feishu, Slack, Discord, Teams, email, and Mattermost.
03Model freedom: OpenAI-compatible APIs, local LLMs, image generation, search, and fallbacks.
04Small core: readable internals with MCP, memory, deployment, and automation built in.
05Own your stack: inspect, customize, self-host, and extend without a giant platform.
04

Use Cases

AI-Gateway logoAI-Gateway
↳Manage and control access to Large Language Models with enterprise-grade policies
↳Enable secure tool access with MCP protocol and function calling
↳Build and control agentic applications with orchestration frameworks
nanobot logonanobot
↳Running long-horizon goals and scheduled automations.
↳Connecting to various chat applications like Telegram, Discord, Slack for AI interaction.
↳Exposing a Python SDK and OpenAI-compatible API for custom integrations and development.
↳Deploying as a long-running local or server-side agent gateway.
05

Best For

AI-Gateway logoAI-Gateway
—
nanobot logonanobot
Most PopularEssential
FAQ

FAQ

What is the difference between AI-Gateway and nanobot?
Both AI-Gateway and nanobot are in the Multi-Agent category. AI-Gateway has 1.0k stars, while nanobot has 49.3k stars.
Which is better, AI-Gateway or nanobot?
The best choice depends on your use case. Choose AI-Gateway if Manage and control access to Large Language Models with enterprise-grade policies, and nanobot if Running long-horizon goals and scheduled automations..
Is AI-Gateway free or open source?
Yes, AI-Gateway is open source on GitHub (MIT).
Is nanobot free or open source?
Yes, nanobot is open source on GitHub (MIT).
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