LAD
How AI agents find each other on local networks
LAD launched on January 29, 2026 with 7 votes, #1,609 of 14,584 launches that month and more than 90% of that year's launches.
What it does
A2A (Google's agent-to-agent protocol) handles how agents talk to each other. MCP handles how agents use tools. But neither answers a basic question: how do you find agents in the first place? So I built LAD-A2A, a simple discovery protocol. When you connect to a Wi-Fi, your agent can automatically find what's available using mDNS (like how AirDrop finds nearby devices) or a standard HTTP endpoint.
Open protocol for discovering A2A-capable AI agents on local networks using mDNS, DNS-SD, and well-known endpoints. Works with hotels, offices, hospitals, and IoT.
An open protocol for discovering A2A-capable agents on local networks. When a device joins a network—hotel Wi-Fi, office LAN, cruise ship, hospital campus—how does the user's AI assistant discover and connect to local agents? LAD-A2A is the first handshake . It answers "who's here?" so that A2A can answer "what can you do?" cd demo cp .env.example .env # Add your OpenAI API key to .env ./run_demo.sh Open http://localhost:8000 to see: cd reference pip install -e . # Start a discovery server (development only) python -m server.lad_server --name "My Agent" --port 8080 # Discover agents. --no-verify-tls opts into plaintext for local dev; without it # the client refuses non-https URLs (a…from lad-a2a.org
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