Explore A2A Protocol implementations, example projects, and tools to start building interoperable AI agent systems
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Verified implementations and examples from the A2A Protocol team
An expense reimbursement agent built with Google Agent Development Kit (ADK). Showcases multi-turn interactions and webform handling through the A2A protocol.
A currency conversion agent built with LangGraph. Showcases multi-turn interactions, tool usage for currency exchange via Frankfurter API, and streaming updates.
An image generation agent built with CrewAI. Showcases text-to-image generation using Google Gemini API and returning images as artifacts through the A2A protocol.
Location-aware agent services with support for geocoding, reverse geocoding, and place search functionality.
Rich place data service for agents, including business information, reviews, and real-time popularity data.
A robust Python implementation of the A2A protocol with Pydantic v2 and dataclass model implementations. Provides type-safe communication between agents.
A minimalistic Python SDK for Agent-to-Agent communication. Features include client/server implementations, streaming responses, and push notifications.
An expense reimbursement agent built with Google Agent Development Kit (ADK). Showcases multi-turn interactions and webform handling through the A2A protocol. This agent helps automate the process of submitting and tracking business expense claims.
A tool for travelers to understand receipts in foreign languages. Uses Gemini AI to scan receipts, extract information, and translate content for easy expense tracking during international travel.
A Python tool that automates the expense submission process for transportation receipts. Takes screenshots of CalTrain tickets and uploads them to SAP Concur under a new expense report, streamlining reimbursement workflows.
A browser-based tool that uses optical character recognition to scan receipts and automatically calculate expenses. Leverages Tesseract.js to extract text from receipt images for simplified expense management.
An image generation agent built with CrewAI. Showcases text-to-image generation using Google Gemini API and returning images as artifacts through the A2A protocol. Enables seamless integration of image generation into A2A agent workflows.
A JavaScript-based image generation service built with Genkit. This agent demonstrates how to handle file artifacts in the A2A protocol, supporting text prompts to generate and return images with appropriate metadata.
A currency conversion agent built with LangGraph. Showcases multi-turn interactions, tool usage for currency exchange via Frankfurter API, and streaming updates through the A2A protocol. Provides real-time conversion between global currencies.
A full-stack finance AI Python bot designed for cross-border payments. This platform features an AI-powered chatbot to guide users through complex payment processes and navigate international compliance requirements.
A dynamic currency conversion application built with Streamlit, providing real-time exchange rates and conversion functionality through an intuitive web interface. Demonstrates how to build financial tools with modern Python frameworks.
A lightweight currency conversion tool focused on simplicity and ease of use. This project demonstrates how to build financial tools that can be easily integrated into A2A workflows, providing straightforward currency conversion capabilities.
The A2A protocol is constantly evolving through community contributions. We welcome projects that showcase innovative implementations and extensions of the protocol.
Have you built something using the A2A protocol? Submit a pull request to the awesome-a2a repository to showcase your work.
Learn how to contribute →Have ideas for improving the A2A protocol? Join discussions in the issues section of the GitHub repository.
Join the discussion →Help improve the documentation to make A2A more accessible to new developers and users.
View documentation →An open-source implementation of a vector store that follows the A2A protocol for efficient retrieval augmented generation. Enables AI agents to access and query vector databases through standardized communication.
A React-based chat interface that supports the A2A protocol natively, making it easy to integrate various A2A agents into a unified chat experience. Features include streaming responses, file sharing, and multi-agent conversations.