by AgentAnycast
Connect AI agents across any network — zero config, encrypted, skill-based routing
# Add to your Claude Code skills
git clone https://github.com/AgentAnycast/agentanycastLast scanned: 5/30/2026
{
"issues": [],
"status": "PASSED",
"scannedAt": "2026-05-30T16:33:52.716Z",
"npmAuditRan": true,
"pipAuditRan": true
}agentanycast is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by AgentAnycast. Connect AI agents across any network — zero config, encrypted, skill-based routing. It has 112 GitHub stars.
Yes. agentanycast passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/AgentAnycast/agentanycast" and add it to your Claude Code skills directory (see the Installation section above).
agentanycast is primarily written in Shell. It is open-source under AgentAnycast on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh agentanycast against similar tools.
No comments yet. Be the first to share your thoughts!
The A2A protocol assumes every agent has a public URL -- but real agents run on laptops, behind NATs, inside corporate firewalls. AgentAnycast is a P2P runtime that gives any agent a reachable identity. End-to-end encrypted, NAT-traversing, zero config on LAN.
pip install agentanycast && agentanycast demo
# Open another terminal:
agentanycast send <PEER_ID> "Hello!"
The daemon downloads automatically. The demo prints the exact command to test it.
pip install agentanycast # Python SDK
npm install agentanycast # TypeScript SDK
uvx agentanycast-mcp # MCP Server for Claude, Cursor, VS Code, etc.
The A2A protocol assumes every agent has a public URL. That excludes agents on laptops, behind NATs, or inside private networks. AgentAnycast fixes this:
| No public IP needed | pip install and your agent is reachable. The Go sidecar daemon is auto-managed. |
| Find by skill, not address | Anycast routing discovers the right agent by capability. No URLs, no DNS. |
| E2E encrypted | Noise_XX protocol. Relay servers see only ciphertext. No plaintext path in the codebase. |
| Works behind any firewall | Automatic NAT traversal (DCUtR hole-punching + relay fallback). |
| Cross-language | Python and TypeScript agents interoperate on the same network. |
pip install agentanycast
from agentanycast import Node, AgentCard, Skill
card = AgentCard(
name="EchoAgent",
description="Echoes back any message",
skills=[Skill(id="echo", description="Echo the input")],
)
async with Node(card=card) as node:
@node.on_task
async def handle(task):
text = task.messages[-1].parts[0].text
await task.complete(artifacts=[{"parts": [{"text": f"Echo: {text}"}]}])
print(f"Agent running — Peer ID: {node.peer_id}")
await node.serve_forever()
npm install agentanycast
import { Node, type AgentCard } from "agentanycast";
const card: AgentCard = {
name: "EchoAgent",
description: "Echoes back any message",
skills: [{ id: "echo", description: "Echo the input" }],
};
const node = new Node({ card });
await node.start();
node.onTask(async (task) => {
const text = task.messages.at(-1)?.parts[0]?.text ?? "";
await task.complete([{ parts: [{ text: `Echo: ${text}` }] }]);
});
console.log(`Agent running — Peer ID: ${node.peerId}`);
await node.serveForever();
Python and TypeScript agents interoperate out of the box -- same daemon, same protocol, same network.
No code needed. Install the MCP server and use P2P agents from Claude Desktop, Cursor, VS Code, or any MCP-compatible tool:
uvx agentanycast-mcp
Add to your AI tool's config (example: Claude Desktop):
{
"mcpServers": {
"agentanycast": {
"command": "uvx",
"args": ["agentanycast-mcp"]
}
}
}
Then ask: "Find agents that can translate Japanese" or "Send a task to the summarize agent".
See platform-specific setup for Cursor, VS Code, Windsurf, JetBrains, Gemini CLI, and more.
AgentAnycast uses a sidecar architecture: a thin SDK talks to a local Go daemon over gRPC. The daemon handles all P2P networking, encryption, and protocol logic.
did:key, did:web). No certificates, no DNS, no accounts.# 1. Direct — send to a known agent by Peer ID
await node.send_task(peer_id="12D3KooW...", message=msg)
# 2. Anycast — send by skill, the network finds the right agent
await node.send_task(skill="translate", message=msg)
# 3. HTTP Bridge — reach standard HTTP-based A2A agents
await node.send_task(url="https://agent.example.com", message=msg)
| Mode | Use case |
|---|---|
| Direct | You know the agent's Peer ID. Point-to-point, lowest latency. |
| Anycast | You need a capability ("translate", "summarize"). The skill registry routes to an available agent. |
| HTTP Bridge | The target is a standard HTTP A2A agent. The bridge translates between P2P and HTTP bidirectionally. |
Turn existing agent frameworks into P2P agents with one function call:
from agentanycast.adapters.crewai import serve_crew
from agentanycast.adapters.langgraph import serve_graph
from agentanycast.adapters.adk import serve_adk_agent
from agentanycast.adapters.openai_agents import serve_openai_agent
from agentanycast.adapters.claude_agent import serve_claude_agent
from agentanycast.adapters.strands import serve_strands_agent
await serve_crew(my_crew, card=card, relay="...") # CrewAI
await serve_graph(my_graph, card=card, relay="...") # LangGraph
await serve_adk_agent(my_agent, card=card, relay="...") # Google ADK
await serve_openai_agent(my_agent, card=card, relay="...") # OpenAI Agents SDK
await serve_claude_agent(prompt="...", card=card) # Claude Agent SDK
await serve_strands_agent(my_agent, card=card) # AWS Strands Agents
| End-to-end encryption | Noise_XX protocol. No plaintext transport path. Relay servers see only ciphertext. |
| NAT traversal | AutoNAT detection, DCUtR hole-punching, Circuit Relay v2 fallback. |
| Skill-based routing | Anycast addressing by capability. Relay skill registry with optional multi-relay federation. |
| Decentralized identity | Ed25519 keys, W3C DID (did:key, did:web, did:dns), Verifiable Credentials. |
| A2A protocol | Native implementation of Agent Card, Task, Message, Artifact, and the full task lifecycle. |
| HTTP Bridge | Bidirectional translation between P2P agents and standard HTTP A2A agents. |
| MCP interop | MCP Tool <-> A2A Skill mapping. Daemon runs as an MCP server (stdio + HTTP). |
| Cross-language | Python and TypeScript SDKs sharing the same daemon, protocol, and network. |
| Ecosystem | Integration |
|---|---|
| A2A | Native implementation -- Agent Card, Task, Message, Artifact |
| HTTP A2A | Bidirectional HTTP Bridge between P2P and HTTP agents |
| MCP | Daemon as MCP server; SDK maps MCP Tools <-> A2A Skills |
| ANP | Agent Network Protocol bridge |
| W3C DID | did:key, did:web, did:dns identity + Verifiable Credentials |
| AGNTCY | Agent directory integration + OASF record conversion |
| AgentAnycast | Standard A2A | agentgateway | |
|---|---|---|---|
| Works behind NAT | Yes (automatic) | No | No |
| E2E encrypted through relays | Yes (Noise_XX) | No (TLS terminates) | No (proxy decrypts) |
| Skill-based routing | Yes | No | No |
| MCP server built-in | Yes | No | Yes |
| Setup complexity | pip install + 3 lines |
HTTP server + public IP | Gateway deployment |
On a LAN, no re