AI Agent Interoperability Standards Emerge
Two protocols are gaining traction to standardize how AI agents communicate and access tools. The Model Context Protocol (MCP) aims to create a standard for LLM applications to access external resources, allowing developers to build tool connections once for use with any model. Similarly, the Agent2Agent (A2A) Protocol is being positioned as a standard for connecting agents built with different frameworks, eliminating the need for custom integrations.
- The Model Context Protocol (MCP) was initially developed by Anthropic and open-sourced in November 2024 to standardize how AI models connect to external data and tools. It functions like a "USB-C port for AI," aiming to replace fragmented, custom integrations with a single, universal protocol. - Google originally developed the Agent2Agent (A2A) protocol to address challenges in large-scale, multi-agent systems and released it as an open-source project in April 2025. It has since been contributed to the Linux Foundation, with IBM's own Agent Communication Protocol being merged into it. - MCP and A2A are designed to be complementary; MCP focuses on connecting an agent to tools and data, while A2A enables communication and collaboration between different agents. An agent might use MCP to access a database and then use A2A to pass the retrieved information to another specialized agent for analysis. - The A2A protocol uses a standardized "Agent Card" in JSON format to help agents discover and understand each other's capabilities. This allows for a more dynamic and flexible multi-agent system where agents can find and interact with each other on the fly. - MCP's architecture is inspired by the Language Server Protocol (LSP) used in software development, which standardizes communication between code editors and language-specific servers. It uses JSON-RPC 2.0 messages for communication between hosts (the LLM application), clients (connectors), and servers (the external tools or data). - The A2A protocol supports both immediate task completion and long-running tasks that might take hours or days, allowing for asynchronous updates through webhooks. For real-time updates or large outputs, the protocol also supports streaming using server-sent events (SSE). - Major technology companies are contributing to the development and adoption of these protocols. SDKs for MCP are maintained in collaboration with partners like Google, Microsoft, and JetBrains. Frameworks like LangChain are also implementing support for the A2A protocol. - Other standards are also emerging in the agent interoperability space, such as the Open Agentic Schema Framework (OASF) and LangChain's own Agent Protocol, which defines a REST API for invoking agents as services. These protocols are seen as complementary building blocks for a robust and scalable AI agent ecosystem.
