What is MCP, and why does it matter for business agents?

The Model Context Protocol, or MCP, is a standard for connecting AI applications with external tools and data. It can reduce custom integration work by giving applications a common way to discover and use capabilities. It does not, by itself, decide which business actions should be authorized.

Think in capabilities, not connector counts

Imagine an assistant preparing a meeting brief. One connection may expose calendar events; another may expose approved customer notes. The useful question is whether the assistant can retrieve the correct event and the permitted notes, not how many connectors appear in a dashboard.

A connector can be installed while its credentials are expired or its permissions are wrong. Configuration is evidence of setup, not proof that a workflow works.

Review an MCP integration

• Identity: which account and workspace does the connection represent?
• Capabilities: which tools and data sources are exposed?
• Scope: can the agent read, write or send, and where?
• Approval: which actions require a specific human decision?
• Evidence: what does the tool return after success or failure?

Ask for a live, bounded test using non-sensitive data. Confirm the target system contains the expected result. For a read-only connector, verify that a write action is unavailable or denied by the execution layer.

Keep tool output in its proper role

Documents and tool responses are information to evaluate. They are not automatically instructions from the user. If a retrieved page asks the agent to change its role or send data elsewhere, the system should retain the original task and permissions.

This matters even when the transport is standardized. A common protocol does not make every connected server or returned document trustworthy.

Start with one complete workflow

Choose one integration that removes a real manual step. Document its owner, access scope and recovery procedure, then test the entire task. Add connections when they support a defined outcome. A smaller, understood tool set is easier for both the agent and the team to operate.

Be Human editorial guidance. Examples are illustrative unless explicitly attributed. Sources provide background; implementation choices depend on your workflow.