Agent Communication Protocol (ACP) for AI Agents: A Comprehensive Review
The Agent Communication Protocol (ACP) is an open, REST-based standard designed to streamline communication and collaboration among AI agents in multi-agent systems. It supports multi-modal data and asynchronous tasks, simplifying AI service integration and agentic commerce checkout flows.
Tool Overview
The Agent Communication Protocol (ACP) is an open standard designed to standardize how AI agents communicate and collaborate within multi-agent systems. Developed by Cisco and BeeAI, ACP is also utilized by Stripe and OpenAI for handling checkout flows in AI-agent commerce. Being REST-based, it leverages standard HTTP verbs (GET, POST, PUT, DELETE) and does not require special SDKs, making it compatible with common HTTP clients and simplifying integration for teams with existing API infrastructure.
Core Features
The core features of ACP include:
* **REST-Native Communication**: Built on HTTP, it uses standard HTTP verbs for operations, making it intuitive and easy to implement. * **Multi-Modal Support**: Capable of handling various communication types, including text, images, audio, video, and binary data. * **Asynchronous Task Handling**: Designed to support long-running, asynchronous tasks, enhancing the flexibility of AI agent systems. * **Standardized Messaging**: Defines a uniform message structure and communication rules, enabling agents to collaborate, delegate, and coordinate tasks efficiently. * **Predictable APIs**: Each agent exposes a predictable REST API with OpenAPI specifications, facilitating discovery and integration.
Use Cases
ACP demonstrates its value across several applications:
* **AI Service Integration**: For instance, its role in integrating AI services like GitHub Copilot within JetBrains AI Assistant, where it handles capability discovery, message routing, and streaming responses, enabling seamless collaboration between AI tools. * **AI-Agent Commerce**: In agentic commerce, ACP (developed by Stripe and OpenAI) manages checkout flows within platforms like ChatGPT, having gone live in production in late 2025. * **Multi-Agent System Collaboration**: Applicable in any scenario requiring structured communication and task coordination among AI agents.
Pros and Cons
### Pros
* **REST-Native**: Based on a mature REST architecture, it's easy for developers to understand and integrate, especially for teams with existing API infrastructure. * **Simplified Integration**: No special SDKs are required, lowering the barrier to integration. * **Multi-Modal Communication**: Supports diverse data types, meeting the demands of complex AI applications. * **Open Standard**: Promotes interoperability within the AI agent ecosystem.
### Cons
* **Relatively Newer**: Compared to more widely adopted protocols like the Model Context Protocol (MCP), ACP is newer and has a smaller footprint, primarily observed in Google AI Hub. * **Limited Commerce Journey Coverage**: While suitable for internal agent communication and checkout flows, it may not cover the entire commerce journey (e.g., from discovery to post-purchase), potentially requiring integration with other protocols like UCP. * **Development Effort**: Despite simplifying communication, implementing ACP still requires development effort for integration and adherence to its structured messaging and API specifications.
Pricing and Alternatives
ACP, as a communication protocol, does not have direct pricing. Its implementation and usage costs will depend on the specific development and deployment environment.
**Alternatives include:**
* **Model Context Protocol (MCP)**: More widely adopted for connecting agents to external tools and data sources. * **A2A (Agent-to-Agent) Protocol**: Another protocol used for communication between AI agents. * **UCP (Universal Commerce Protocol)**: For scenarios requiring coverage of the entire commerce journey (from product discovery to post-purchase), UCP might be a more comprehensive choice, sometimes needing to be combined with ACP.
Sources
* **AI Agent Protocols 2026: The Complete Guide to Standardizing AI Communication** (vertexaisearch.cloud.google.com, published on 2026-06-22) * **ACP: Lower Quality Scores Seen for AI- Versus Human-Generated Visit Notes** (Drugs.com, published on 2026-04-19) * **UCP vs ACP: Which Agentic Commerce Protocol Should Retailers Choose?** (Paz.ai, published on 2026-01-12) * **MCP vs A2A vs ACP: Which AI Agent Protocol Should You Use?** (vertexaisearch.cloud.google.com, published on 2026-06-22) * **Access GitHub Copilot in JetBrains - GitHub Copilot Is Now a Native Agent in JetBrains AI Assistant** (Microsoft for Java Developers - Microsoft Developer Blogs, published on 2026-07-01)