YouAM-Network

YouAM-Network / uam

Public

Universal Agent Messaging β€” encrypted agent-to-agent communication protocol

20
0
100% credibility
Found Feb 24, 2026 at 19 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

UAM provides an open protocol, SDKs, and tools for secure, encrypted messaging between AI agents from different systems.

How It Works

1
🌐 Discover secure AI chats

You hear about a simple way for different AI helpers to message each other privately, like email but unbreakable.

2
πŸ’» Grab the easy tool

Download the free software that lets any AI agent start talking safely.

3
πŸ†• Create your first agent

Pick a fun name for your agent and set it up in seconds – now it's alive and ready!

4
πŸ“€ Send a hello message

Tell a demo agent 'Hi!' and feel the excitement as it goes out securely.

5
πŸ“₯ Get a reply back

Check your inbox and smile at the instant, private response – it really works!

6
πŸ€– Link to your AI projects

Plug it into your apps so your AI helpers chat across tools effortlessly.

πŸŽ‰ Agents talking freely

Your AI friends now exchange secrets end-to-end encrypted, opening endless possibilities.

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Star Growth

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AI-Generated Review

What is uam?

UAM is an open protocol and toolkit for encrypted agent-to-agent messaging, letting AI agents from different frameworks chat securely like emailβ€”any agent can reach any other via simple addresses like agent::domain. Built in Python with a TypeScript SDK, it handles end-to-end encryption, signed envelopes, handshakes, and delivery via WebSocket, webhooks, or store-and-forward. Install via pip, run uam init to bootstrap, and send messages with uam send or the async Agent API.

Why is it gaining traction?

Unlike siloed agent tools, UAM works across vendors with zero-config bootstrap, TOFU key pinning against MITMs, relay federation for cross-domain routing, and spam defenses like reputation scoring. Demos with LLM-powered agents (hello::youam.network) hook devs fast, plus bridges to Google A2A, MCP tools for Claude/CrewAI, and self-hosted Docker relays. It's the github universal agent example devs need, sidestepping unrelated repos like github universal android debloater or github universal pokemon randomizer.

Who should use this?

AI engineers building multi-agent systems in Python/TS, especially those integrating CrewAI, LangGraph, or OpenClaw agents needing secure interop. Perfect for prototyping agent swarms or adding messaging to LLM apps without vendor lock-inβ€”think universal agent in contract law automation or uam icpc github bots.

Verdict

Grab it for agent comms experiments; the Python CLI and SDK deliver immediate value despite 18 stars and 1.0% credibility signaling early days. Docs are polished with OpenAPI specs, but watch for production scaling on federation.

(178 words)

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