An integration is useful when it carries the right context and respects the same access boundary as the user interface.
API and MCP serve different interfaces
APIs connect approved software workflows. MCP can expose selected tools and context to an AI client. Neither interface should bypass tenant permissions, approval requirements or the recorded history of consequential actions.
Private AI remains accountable to people
A model can help draft a project plan or identify missing information. It must not independently approve people, make compliance determinations or use a connector to escape a required human review.
Private model execution and full network isolation are different promises. Model services, email, identity checks, timestamping, telemetry and mobile notifications must each be assessed within the deployment design.
The documented MCP tool catalogue is read-only. Deployment setup, client compatibility and available tools are confirmed per engagement. Explore integrations, examples and connection options ↗