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docs: restructure README with comparison table, badges, and roadmap
- Add PyPI/npm download badges and GitHub Discussions badge
- Add emoji feature highlights and problem statement table
- Add comparison table vs HTTP A2A, ngrok, and direct TCP
- Add framework integration matrix and public roadmap
- Add examples index linking to all 5 example directories
AgentAnycast is a decentralized P2P runtime for the [A2A (Agent-to-Agent)](https://github.com/a2aproject/A2A) protocol, powered by [libp2p](https://libp2p.io/). It lets AI agents securely communicate across any network — your laptop, a corporate server, or the other side of the internet — without public IPs, VPNs, or any infrastructure setup.
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Same A2A semantics you already know (Agent Card, Task, Message, Artifact), with automatic NAT traversal and end-to-end encryption built in.
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- 🔒 **End-to-end encrypted** — Noise_XX protocol. Relay servers see only ciphertext.
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- 🌐 **NAT traversal built in** — AutoNAT + DCUtR + Circuit Relay. Works from behind any firewall.
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- 🎯 **Skill-based routing** — Send tasks by capability, not by address. The network finds the right agent.
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- 🔌 **Framework adapters** — One-line integration with CrewAI, LangGraph, and MCP tools.
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- 🪪 **Decentralized identity** — Ed25519 keys + W3C DID:key. No certificates, no DNS, no accounts.
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- 🚀 **Zero config** — `pip install agentanycast` and you're live. The daemon is auto-managed.
A2A requires every agent to be an HTTP server with a public URL. This excludes most real-world agents:
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[A2A](https://github.com/a2aproject/A2A) is the emerging standard for agent-to-agent communication — but it requires every agent to be an **HTTP server with a public URL**. This excludes most real-world agents:
-**Agents behind firewalls** — corporate networks don't expose internal services to the internet
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-**Privacy-sensitive agents** — routing prompts through a centralized gateway is a non-starter
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No mainstream agent framework solves this. They all assume agents share the same process or the same cloud. **AgentAnycast is the transport layer that closes this gap.**
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No mainstream agent framework solves cross-network communication. They all assume agents share the same process or cloud. AgentAnycast is the transport layer that closes this gap.
This project provides an [`llms.txt`](llms.txt) file for AI agent discoverability and a [`.cursorrules`](.cursorrules) file for Cursor IDE integration.
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## Contributing
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We welcome contributions! See [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.
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