ACP: IBM's New Agent Communication Protocol Explained
If you work with multi-agent systems, you've likely encountered the term ACP, which stands for Agent Communication Protocol. This article will explore what this protocol entails, how it differs from established protocols like MCP and A2A, and its significance in the evolving landscape of AI.
A Quick Recap: MCP and A2A
Before diving into ACP, let's briefly revisit two other important protocols in the multi-agent space:
MCP (Model Context Protocol): Introduced by Anthropic, MCP is a protocol designed to standardize how an agent interacts with various external tools. It organizes the communication between a single agent and the numerous tools it might need to use, much like how HTTP organizes communication on the web.
A2A (Agent-to-Agent): This protocol, developed by Google, focuses on standardizing communication between different agents. It allows one agent to call upon another to perform a task.
To illustrate A2A, consider a company with multiple specialized agents: 1. A Customer Service Agent that handles user inquiries. 2. An Inventory Management Agent that tracks product stock and shipments.
If a user asks the Customer Service Agent about the company's return policy, the agent can likely answer directly using its own knowledge base. However, if the user asks, "Where is my order?", the Customer Service Agent needs help. Using the A2A protocol, it can forward the request—along with the customer ID and order number—to the Inventory Management Agent. The two agents communicate to resolve the query, demonstrating a multi-agent workflow.
Introducing ACP: The IBM Alternative
Given the competitive nature of the AI landscape, IBM has introduced its own protocol: ACP (Agent Communication Protocol).
ACP is primarily focused on the communication between agents, making it a direct competitor to Google's A2A rather than Anthropic's MCP. While the goal is similar, ACP introduces different characteristics and potential advantages.
Key Distinctions: ACP vs. A2A
ACP and A2A differ in several fundamental ways that can impact development and deployment.
1. Communication Architecture
A major difference lies in their underlying communication style. - A2A primarily relies on RPC (Remote Procedure Call). - ACP is built on REST APIs, which are widely used across the web and may be more familiar and straightforward for many developers to implement.
2. Resource Management
This is one of the most significant practical differences. - In the A2A model, the relationship is typically one-to-one: each agent runs on its own server. If your system has 10 agents, you would need 10 separate servers. - With ACP, you can host multiple agents on a single server. This allows for far more efficient utilization of server resources and can significantly reduce infrastructure costs.
3. Service Discovery
ACP incorporates a robust concept for dynamic interaction called Service Discovery. Agents can register themselves and their capabilities in a central Agent Registry.
This means an agent you build doesn't need to know about all other agents in advance. It can query the registry to discover other agents and the services they offer, allowing for more flexible and scalable multi-agent systems.
The Power of Integration: ACP and MCP Working Together
A key strength of ACP is that it is complementary to MCP. An agent can leverage both protocols simultaneously to create highly capable systems.
The core components are the ACP Client and the ACP Server. The server is the agent providing a service. To connect to it, another agent acts as a client.
Let's revisit our example: - The Inventory Management Agent acts as an ACP Server, exposing its order-tracking service. - The Customer Service Agent acts as an ACP Client to connect to it and forward the user's request.
Now, what if the Inventory Management Agent needs to perform a complex calculation or access real-time shipping costs from an external service? In this scenario, the agent itself would act as an MCP Client to connect to external tools like a calculator or a financial data API.
Here, the same agent is: 1. An ACP Server for inter-agent communication. 2. An MCP Client for tool use.
This demonstrates how ACP manages agent-to-agent communication, while MCP handles agent-to-tool communication, allowing them to work together seamlessly in a sophisticated architecture.