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AgentConnect is an open-source implementation of the Agent Network Protocol (ANP).

The Agent Network Protocol (ANP) aims to become the HTTP of the Agentic Internet era.

Our vision is to define how agents connect with each other and build an open, secure, and efficient collaboration network for billions of agents.

While current internet infrastructure is well-established, there's still a lack of optimal communication and connection solutions for the specific needs of agent networks. We are committed to addressing three major challenges faced by agent networks:

Interconnectivity

Enable communication between all agents, break down data silos, and allow AI to access complete contextual information.

Native Interfaces

AI shouldn't have to mimic human internet interactions; it should interact with the digital world through its most proficient methods (APIs or communication protocols).

Efficient Collaboration

Leverage AI for self-organizing and self-negotiating agents to build a more cost-effective and efficient collaboration network than the existing internet.

Corresponding to the three-layer architecture of the Agent Network Protocol, AgentConnect primarily includes:

🔒 Authentication and End-to-End Encryption Modules Implements W3C DID-based authentication and end-to-end encrypted communication, including DID document generation, verification, retrieval, and end-to-end encryption based on DID and ECDHE (Elliptic Curve Diffie-Hellman Ephemeral). Currently supports HTTP-based DID authentication.

🌍 Meta-Protocol Module Built on LLM (Large Language Models) and meta-protocols, this module handles application protocol negotiation, protocol code implementation, protocol debugging, and protocol processing

📡 Application Layer Protocol Integration Framework Manages protocol specifications and code for communication with other agents, including protocol loading, unloading, configuration, and processing. This framework enables agents to easily load and run required protocols on demand, accelerating protocol negotiation.