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AI integration standards

Interfaces and standards connecting applications · models · tools · data · agents.

For: Developers · technical learners.

After this page you can: Identify which interface or standard an integration needs.

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Part of: Artificial Intelligence

About AI integration standards

AI integration standards are agreements about how software discovers capabilities, sends requests, carries data, and applies access controls across an integration boundary. Start by asking what is connecting to what: an application calling a service, an AI application using tools or application context, an editor working with a coding agent, or one agent service handing a task to another. These boundaries call for different interfaces, even when each is casually described as an agent protocol. A useful choice starts with the peer roles, message shape, transport, discovery, and access checks the integration needs.

Begin with the interface and access vocabulary, then compare Model Context Protocol, using specification revision 2026-07-28, which covers application-facing tools and context, with agent interoperability, which covers agent-to-agent, editor-agent, and portable skill interfaces. As you assess an integration, write down its caller and callee, whether it needs replies, streams, or task updates, how capabilities are discovered, and who grants access. Then check which revision, bindings, and optional features both endpoints support.

Start here

route

Start with the interface choices

Read the MCP overview, then use the practice questions to distinguish application-to-tool integrations from agent-to-agent and editor-agent integrations.

Start with: Model Context Protocol overview

Learn the foundations

1.Choose the interface and control accessAn API is the software contract a component exposes to other software.

An API is the software contract a component exposes to other software. JSON-RPC defines a lightweight, transport-agnostic way to make remote procedure calls using JSON. OAuth is for delegated access to protected resources; it does not, by itself, describe the operations an application offers. Authentication establishes or verifies an asserted identity, while authorization determines whether that identity may access a resource or perform an action. For a concrete integration, first identify the operations and data being exposed, then decide how requests are represented and how the caller’s identity and permissions are checked. These are related interface decisions, but they answer different questions.

API

A defined software interface through which one component can interact with another component’s capabilities.

JSON-RPC

A lightweight, transport-agnostic remote procedure call protocol that uses JSON as its data format.

OAuth

A framework that lets a third-party application obtain limited access to an HTTP service, with a resource owner’s approval or on its own behalf.

Authentication

Verifying credentials and the identity they assert.

Authorization

Deciding whether an authenticated party has permission to access a particular resource or service.

Try it

For a service integration, write one sentence each explaining what an API contract, JSON-RPC, and OAuth answer.

The API defines the software interface; JSON-RPC defines a JSON-based method-call protocol; OAuth supports delegated, limited access to a protected HTTP service.

2.Connect an AI application to tools and dataUse Model Context Protocol (MCP) when an AI application needs a shared contract for tools, resources, or prompts.

Use Model Context Protocol (MCP) when an AI application needs a shared contract for tools, resources, or prompts. In MCP specification revision 2026-07-28, tools let servers expose operations that models can invoke, resources let servers share context with clients, and the overview identifies prompts as a server feature. The revision’s lifecycle is stateless: requests carry their metadata, and state that must span requests is referenced by an explicit identifier. Its standard transports are stdio and Streamable HTTP; choose based on how the peers communicate, then verify the actual client and server support the selected transport and features. MCP authorization is optional; for HTTP transports, the specification defines an authorization flow, while STDIO implementations retrieve credentials from the environment.

  • Transports

    Compare the standard transport bindings and what each binding carries.

  • Authorization

    Check how authorization requirements differ between HTTP-based and STDIO transports.

Try it

For an MCP integration targeting revision 2026-07-28, choose a transport for a client-launched local subprocess and for a remote HTTP endpoint.

Use stdio for the client-launched subprocess and Streamable HTTP for the remote HTTP endpoint.

3.Connect agents, editors, and portable skillsChoose Agent2Agent (A2A) version 1.0.0 when independent agent systems need to communicate and discover one another; its Agent Card describes the server’s ident…

Choose Agent2Agent (A2A) version 1.0.0 when independent agent systems need to communicate and discover one another; its Agent Card describes the server’s identity, capabilities, skills, and interaction requirements. Choose Agent Client Protocol (ACP) v1 when connecting a code editor client with a coding agent: its overview describes JSON-RPC methods and notifications, session setup, prompt turns, and permission requests. Agent Skills provides a portable directory format built around a required SKILL.md file, with optional scripts, references, and assets. These interfaces address different peers and exchange patterns. Check the current protocol version, advertised capabilities, authentication requirements, and supported operations for both endpoints before designing the handoff.

Try it

Choose a protocol for each case: an editor communicating with its coding agent, and one independent remote agent handing a task to another.

Use ACP v1 for the editor-to-coding-agent interface and A2A for communication between independent agent systems.

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