IBM Agent Communication Protocol
IBM has declared the release of its Agent Communication Protocol (ACP), an open standard intended to facilitate the smooth connection and cooperation of AI agents constructed using various frameworks and technology stacks. IBM hopes that Agent Communication Protocol, which serves as a core layer for interoperability, will become the “HTTP of agent communication,” giving AI agents a common language to do intricate, real-world activities.
Given that agents frequently operate as isolated “islands” in the existing Artificial Intelligence environment, the protocol, which was released on May 28, 2025, tackles a major issue. Custom integrations, which are characterized as costly, fragile, and challenging to scale, are usually needed to bridge the gap between these agents.
Without a common standard, every integration is costly duct tape. By providing a single interface for agents created with platforms like BeeAI, LangChain, CrewAI, or custom code, IBM’s Agent Communication Protocol seeks to do away with the requirement for these kinds of connections.
BeeAI, an open-source platform devoted to finding, executing, and creating AI agents, uses ACP as its foundational protocol. In March, IBM donated BeeAI to the Linux Foundation, a nonprofit organization. Open governance ensures transparency and promotes community-driven growth for both Agent Communication Protocol and BeeAI. With this method, developers may embrace and enhance the standard without worrying about being locked onto a particular manufacturer.
The capacity of Agent Communication Protocol to enhance Anthropic’s Model Context Protocol (MCP) was a fundamental design tenet. MCP has quickly established itself as a standard for agents to access external data and resources. ACP links agents directly to one another, whereas MCP links agents to their resources and expertise, such databases or APIs. BeeAI and any other multi-agent orchestration system may use ACP and MCP in tandem.
IBM Research product manager Jenna Winkler emphasised the need of both protocols for expanding AI systems in the real world. In one scenario, two agents use MCP to collect market data and execute a simulation at the same time. They then use Agent Communication Protocol to compare their outcomes and make a suggestion.
Technically speaking, Agent Communication Protocol supports both synchronous and asynchronous agent interactions and is based on a RESTful design that is implemented over HTTP. Compared to protocols that rely on more intricate communication techniques, this architecture is simpler to use and integrate into production systems since it closely follows common HTTP patterns. In contrast, the communication protocol used by MCP is JSON-RPC.
The fact that developers may communicate directly with agents using common HTTP tools like curl, Postman, or even a web browser makes Agent Communication Protocol easy to utilize. This indicates that while Python and TypeScript SDKs are offered for convenience, a specialized software development kit (SDK) is not necessarily necessary.
By permitting agents to incorporate information into their distribution packages, ACP also makes offline discovery easier. This makes it possible for agents to be located even in secure, disconnected, or scale-to-zero environments. Agent Communication Protocol fully supports synchronous communication for easier use cases and testing, but its primary architecture is asynchronous, making it perfect for lengthy workloads.
Agent Communication Protocol offers new architectural options for multi-agent systems that go beyond technological details. It transcends the conventional “manager” structure, in which one “boss” agent coordinates with others. Agents can communicate with one another directly as peers via ACP, starting discussions or assigning tasks to one another without the need for a middleman. For interactions between agents inside an organization or with agents outside of it, this peer-to-peer capacity is very important.
Either agent should be able to make contact or assign a job, according to Kate Blair, director of product incubation at IBM Research. She gave an example of a triage agent answering consumer enquiries and forwarding the history and interaction to the relevant service agent so they may independently handle the ticket.
IBM Research gave a demonstration of an early version of ACP. A2A, Google’s proprietary agent-to-agent protocol, was introduced shortly after. Blair anticipates more changes as they are evaluated in real-world circumstances, and he feels there is potential for various agent protocols, at least in the early stages, despite the introduction of additional standards.
ACP is a community-led project that promotes developer involvement. The project makes sure there are always tasks available for community members to contribute by holding monthly open community calls and keeping an active GitHub discussion area.