antiv

antiv / mate

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Production-ready multi-agent orchestration engine built on Google ADK. Database-driven agent config, 50+ LLM providers, MCP protocol, persistent memory, web dashboard, RBAC.

agent-orchestration ai-agents dashboard fastapi google-adk
20
1
100% credibility
Found Mar 01, 2026 at 18 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

MATE is a web dashboard for building and managing teams of AI agents that collaborate on tasks using various AI models.

How It Works

1
📦 Discover MATE

You hear about MATE, a friendly tool that lets you build teams of smart AI helpers without any coding.

2
🛠️ Set it up quickly

Download and run a simple command to get everything ready on your computer.

3
🔗 Connect an AI brain

Link your favorite AI service so your helpers can think and respond.

4
✨ Open the web dashboard

A colorful screen appears where you see your AI team and can tweak them easily.

5
👥 Build your AI team

Pick smart helpers, give them instructions, and connect helpful tools like search or images.

6
💬 Start chatting

Talk to your AI team and watch them work together to solve problems.

🎉 Your AI team shines

Your custom AI assistants handle tasks perfectly, saving you time and effort every day.

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Star Growth

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AI-Generated Review

What is mate?

Mate is a Python-based multi-agent orchestration engine built on Google ADK, turning complex agent hierarchies into production-ready systems via a database-driven config and FastAPI web dashboard. It lets you define agents, tools, and 50+ LLM providers (like Ollama or OpenRouter) without code changes, with persistent memory, RBAC, MCP protocol support, and an embeddable chat widget. Developers get quick deploys via Docker Compose or a simple `python auth_server.py`, solving the pain of redeploying for every agent tweak in raw ADK setups.

Why is it gaining traction?

Unlike basic ADK scripts, Mate offers a full web UI for agent trees, token analytics, self-building agents, and project isolation—swap models or add MCP tools live. Production-ready features like auto-migrations, Prometheus metrics, and LiteLLM routing stand out for teams scaling AI agents on GitHub, beating DIY FastAPI production-ready github boilerplate. The widget drops into any site for instant chat, hooking devs tired of custom UIs.

Who should use this?

AI engineers orchestrating multi-agent workflows for research, CV analysis, or creative tasks; ops teams needing RBAC-multi-tenant setups like media mate github or production ready ai agents github. Ideal for startups embedding agent chats (mate translate github style) without building dashboards from scratch.

Verdict

Promising for production ready ai agents github at 11 stars and 1.0% credibility—docs shine with screenshots and MCP guides, 134 tests cover core flows—but it's early; test locally before prod. Grab it if you want ADK without the hassle.

(198 words)

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