What is Agentvault

AgentVault is an open-source toolkit designed for secure and decentralized AI agent interoperability, utilizing A2A (Agent-to-Agent) and MCP (Multi-Channel Protocol). It includes a Python library, a Registry API, and a Command Line Interface (CLI).

Use cases

Use cases for AgentVault include developing collaborative AI systems, managing decentralized agent networks, enhancing AI capabilities through interoperability, and facilitating secure communication in multi-agent environments.

How to use

To use AgentVault, clone the repository from GitHub and follow the installation instructions. You can interact with the toolkit through the CLI, manage agent registrations via the Registry API, and develop AI agents using the Python library.

Key features

Key features of AgentVault include a comprehensive Python library for AI agent development, a secure Registry API for managing agent interactions, a user-friendly Command Line Interface, decentralized architecture for independent agent operation, security measures for safe communication, and interoperability with other AI frameworks.

Where to use

AgentVault can be used in various fields including artificial intelligence research, development of decentralized applications, and any domain requiring secure communication between AI agents.

AgentVault 🛡️

Welcome to AgentVault, an open-source toolkit designed for secure and decentralized AI agent interoperability. This repository includes a Python library, a Registry API, and a Command Line Interface (CLI) that enable seamless communication between AI agents using A2A (Agent-to-Agent) and MCP (Multi-Channel Protocol).

Table of Contents

1. Introduction
2. Features
3. Installation
4. Usage
5. API Documentation
6. Contributing
7. License
8. Support
9. Releases

Introduction

In today’s rapidly evolving landscape of artificial intelligence, interoperability between agents is crucial. AgentVault aims to provide a robust framework for developers and researchers to build, manage, and interact with decentralized AI agents. By leveraging A2A communication, AgentVault facilitates collaboration among agents, enhancing their capabilities and expanding their potential applications.

Features

• Python Library: A comprehensive library that simplifies the development of AI agents.
• Registry API: Manage agent registrations and interactions securely.
• Command Line Interface: Easily interact with the toolkit from the terminal.
• Decentralized Architecture: Supports the development of agents that operate independently while communicating effectively.
• Security: Implements key management practices to ensure secure communication.
• Interoperability: Designed for seamless integration with other AI frameworks and protocols.

Installation

To install AgentVault, follow these steps:

1. Clone the repository:

   git clone https://github.com/hoangtuanhehehehhe/AgentVault.git
   cd AgentVault
   

2. Install the required dependencies:

   pip install -r requirements.txt
   

3. Ensure you have Python 3.8 or higher installed.

4. Optionally, set up a virtual environment to manage dependencies:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`
   

Usage

Basic Commands

To start using AgentVault, you can run the CLI commands directly in your terminal. Here are some basic commands to get you started:

• Initialize a new agent:

  agentvault init <agent_name>
  

• Register an agent:

  agentvault register <agent_name> --api-key <your_api_key>
  

• Send a message between agents:

  agentvault send <from_agent> <to_agent> <message>
  

Example

Here’s a simple example of creating and registering an agent:

# Initialize a new agent
agentvault init MyAgent

# Register the agent
agentvault register MyAgent --api-key my_secure_api_key

API Documentation

For detailed API documentation, please refer to the API Documentation.

Contributing

We welcome contributions from the community. If you want to contribute to AgentVault, please follow these steps:

1. Fork the repository.
2. Create a new branch:

   git checkout -b feature/YourFeature
   

3. Make your changes and commit them:

   git commit -m "Add your feature"
   

4. Push to your fork:

   git push origin feature/YourFeature
   

5. Create a pull request.

Please ensure that your code follows the existing style and includes tests where applicable.

License

AgentVault is licensed under the Apache 2.0 License. See the LICENSE file for details.

Support

If you encounter any issues or have questions, please open an issue in the repository. We will respond as soon as possible.

Releases

To download the latest version of AgentVault, visit the Releases section. Here, you can find the latest binaries and source code. Make sure to download and execute the appropriate files for your platform.

Conclusion

AgentVault represents a significant step towards enabling secure and efficient communication between AI agents. By providing a straightforward toolkit, we aim to empower developers and researchers to explore new possibilities in AI interoperability.

Thank you for your interest in AgentVault! We look forward to seeing what you build.