AI clients, tools, and MCP
Connect AI to systems by understanding tools, authorization, scope, context, and the boundary between a model's reasoning and an application's actual capabilities.
Why this matters
An AI model does not automatically have access to your data or systems. Useful AI integration comes from giving an authorized client specific tools and context with explicit boundaries.
Learn it
An AI client can connect to an MCP server that exposes defined tools or resources. The client discovers what is available, authenticates as required, and invokes a tool using a structured contract. The server—not the model—enforces permissions, tenant/workspace scope, validation, and side effects. Read access and write access should be distinguishable. A handshake or integration test can prove the connection and authorization path before relying on it.
Work through an example
An authorized agent might be allowed to read workspace activity and validate coordinates while being denied write operations. Another manifest can expose additional actions only after human approval.
AI client → MCP connection → tool contract → authorization → server operation → result/auditPractice
- 1Choose one task an AI client should be able to perform and one it should not.
- 2Write the minimum tool inputs and outputs needed for the allowed task.
- 3Identify where authentication, authorization, validation, human review, and audit evidence belong.
Try it
Follow data through a workflow
Select each stage. The goal is to keep the source, connection, protocol, data, spatial context, rule, and use understandable instead of collapsing everything into one box.
The real-world fact, device, file, application, person, or system that starts the workflow. If it is an observation, preserve where, when, what, source, value, units, and provenance.
What to watch for
Do not describe 'the AI' as directly editing a system if the actual architecture is client → authorized tool → server action. Name the boundary honestly.
Where this takes you
This prepares users for AtlasAgents, MCP connections, scoped tools, agent handshakes, and similar integrations with other AI-capable systems.