AI agent integrations connect an AI application to software, data, tools, or other agents so it can retrieve information or take an action beyond generating a reply. A regular API or HTTP connector often fits a conventional service; MCP standardizes access to tools and resources; A2A lets one agent delegate work to another. These approaches can coexist in one system.
What is an AI agent integration?
An integration is a defined connection between an AI application or agent and an external capability. That capability might be a calendar, database, search service, calculator, design application, or another agent. The connection gives the AI a way to obtain information or request an action rather than relying only on what it can produce from its model.
The Model Context Protocol project describes MCP as “an open-source standard for connecting AI applications to external systems.” Its official overview explains how MCP can provide access to tools, APIs, and resources: MCP introduction.
How does an integration work?
The details vary by application and protocol, but a typical interaction follows a simple pattern:
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- Discover capabilities: The application learns what the connected tool, service, or agent can do.
- Route a request: When a user’s task calls for that capability, the application sends an appropriate request to the endpoint.
- Perform the work: The endpoint retrieves information, carries out an action, or handles a delegated task.
- Return a result: The endpoint responds with information or a task outcome that the calling application can use.
- Complete the user’s task: The agent incorporates the result into its response or next action.
This is a high-level model, not a claim that every framework uses identical internals. A tool call may be a discrete operation, while a delegated agent may carry out a workflow and return a broader result.
MCP vs. A2A: what is the difference?
MCP and A2A address different connections. MCP is for connecting an AI application or agent to tools, APIs, data, and resources. A2A—the Agent2Agent protocol—is for communication and task collaboration between agents. The A2A project describes agents as able to interact without sharing their internal memory, tools, or proprietary logic; that does not remove the need to control access and monitor outcomes. See the A2A project documentation.
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| Decision point | MCP | A2A |
|---|---|---|
| What is on the other end? | A tool, API, data source, resource, or workflow | Another agent, often with its own domain-specific reasoning or workflow |
| Main purpose | Access information or invoke a capability | Delegate a task, exchange context, and collaborate across agents |
| Typical examples | Search, database or calendar access, calculators, and application actions | Cross-framework or cross-vendor workflows involving task delegation |
| Key security question | Which tools or resources can be reached, and with what identity and permissions? | Which agent is being called, what data is shared, what it may do, and how its work is monitored? |
These are complementary roles, not an either-or choice. An application might use MCP to give an agent access to tools and A2A to delegate a specialized task to another agent. For protocol-specific details, consult the MCP introduction and the A2A documentation.
When should you use an API, MCP, or A2A?
- Use a direct API or HTTP connector when the endpoint is a conventional service and a straightforward request-and-response connection is enough. Agent-to-agent task exchange is unnecessary for many ordinary integrations.
- Use MCP when an application needs a standardized way to connect to tools, APIs, data sources, or other resources.
- Use A2A when the remote component is an A2A-capable agent and its own reasoning or workflow is useful. The interaction involves assigning it a task and receiving its response, rather than simply invoking a basic service operation.
- Combine approaches when different endpoints call for different interaction patterns. Microsoft says multiple integration models can be used within one Copilot Studio agent; that is a product example, not a requirement for other systems. See Microsoft’s integration-model guidance.
What does deployment look like?
A remote agent must be reachable at an endpoint, and the caller needs a suitable way to authenticate. In a Microsoft Copilot Studio example, an external A2A agent is exposed over HTTPS and can be hosted using Azure App Service or a container. Microsoft presents Dev Tunnels for local development and demonstrations, not production use. These are options in that vendor’s example, not universal hosting requirements. See Microsoft’s A2A agent guidance.
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Availability can also depend on product rollout. Microsoft’s page about Copilot Studio MCP and A2A channels was last updated October 1, 2026, labels the functionality prerelease, and limits availability to early release cycle environments. In the documented setup, Copilot Studio publishes an HTTPS endpoint; clients authenticate with Microsoft Entra ID on behalf of the signed-in user, and access is checked for that user. Those details describe this specific Microsoft configuration and may change as the product evolves. See Microsoft’s MCP and A2A channels documentation.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How do you secure and govern agent integrations?
A protocol defines a way to communicate; it does not automatically make the connected system safe, authorized, or reliable. Treat every integration as a boundary and decide what is permitted to cross it and what the endpoint may do. Microsoft’s guidance for connected agents highlights evaluation of data handling, permissions, trustworthiness, observability, traceability, and human oversight: Microsoft’s A2A agent guidance.
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- Identity and permissions: Decide which users or services can connect and which tools, data, or actions each identity may access.
- Data sharing: Determine what information is sent to an endpoint, how it is handled, and whether sharing is appropriate for the task.
- Trust and reliability: Assess the connected service or agent and the consequences of acting on its result.
- Monitoring and traceability: Make it possible to observe requests and outcomes and determine which identity initiated the work.
- Human oversight: Decide when a person should approve an action or review a result, particularly where an error would have meaningful consequences.
Authentication arrangements are implementation-specific. For example, Microsoft’s documented Copilot Studio channel configuration uses an app registration and delegated permissions, with requests carrying the signed-in user’s identity. That is not a general requirement for every MCP or A2A connection; consult the Microsoft channel documentation for that setup.
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