> ## Documentation Index
> Fetch the complete documentation index at: https://agentcommunicationprotocol.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# MCP and A2A

> How does ACP compare to other AI protocols

## Model Context Protocol

[**Model Context Protocol (MCP**](https://modelcontextprotocol.io/introduction)**)** is a popular open standard from Anthropic that provides AI **models** (usually LLMs) with **context**: resources, tools, etc. MCP operates effectively within the bounds of a "single agent", since it enables the connection between the LLM and its tools/resources.

On the other hand, Agent Communication Protocol (ACP) is a protocol that enables **communication** between **agents**.

MCP and ACP work together to build powerful agentic systems, as shown below:

```mermaid theme={null}
graph TD
    subgraph "Agent 1"
        A1[model] <--> |MCP| B1[tool]
        A1 <--> |MCP| C1[resource]
        A1 <--> |MCP| D1[...]
    end

    subgraph "Agent 2"
        A2[model] <--> |MCP| B2[tool]
        A2 <--> |MCP| C2[resource]
        A2 <--> |MCP| D2[...]
    end

    A1 <--> |ACP| A2

    class Agent1,Agent2 agent;
    class A1,A2 model;
    class B1,B2,C1,C2,D1,D2 mcp;
```

## Agent2Agent Protocol

The Agent Communication Protocol (ACP) launched by IBM in March 2025 and [Agent2Agent Protocol (A2A)](https://github.com/google/A2A), launched by Google in April 2025, both aim to create a standard interface for agent-to-agent communication.

Advantages of ACP include:

* **Open Governance**: Managed through the Linux Foundation.
* **Co-developed with BeeAI**: An open platform to manage the agent lifecycle, including installation, running, registration, and sharing of agents.
* **REST-based Communication**: Enables lightweight, runtime-free agent invocation and scalable system integration.
* **Offline Agent Discovery**: Agents are packaged with details at build time. Note: BeeAI provides an open registry implementation.
* **Message Structure**: The MIME-type-based message structure in ACP is designed to be extensible and flexible, as opposed to the pre-defined types.
* **Agent Support**: Compatible with any agent, from small, stateless, serverless utility agents to long-running, stateful conversational agents.
* **Native SDK**: Allows users to wrap an agent and create a server, provides tooling for session management, and handles agent state management.