MCP FAQ
Common questions about MCP clients, servers, tools, security, adoption, and how MCP differs from Skills.
Is MCP a tool?
No. MCP is not one specific tool. It is a protocol layer that lets AI clients discover and call capabilities exposed by servers.
Do I need an MCP server?
If an AI client needs to access an external system, the server is usually the boundary that exposes that system safely. For simple local experiments, the server can be small; for production systems, it should be treated like infrastructure.
How is MCP different from a normal API?
A normal API is usually built for application code. MCP capabilities are described so an AI client and model can discover when and how to use them. That makes names, descriptions, schemas, permissions, and errors especially important.
Is MCP safe by default?
No protocol makes unsafe capabilities safe automatically. You still need least privilege, validation, approval flows, audit logs, and careful separation between read-only and write actions.
How does MCP relate to Skills?
MCP gives the agent access to capabilities. Skills teach the agent how to perform repeatable tasks. A Skill can instruct the agent to use an MCP tool, but the Skill is not the tool itself.
Where should a beginner start?
Start with one read-only capability, define a clear schema, connect it to a client, and test how the agent chooses and uses it. Then add write actions only after permissions and errors are clear.
What is the difference between a tool and a resource?
A tool performs an action and returns a result. A resource is readable context the agent can inspect. If the model needs to change something, that is a tool; if it only needs to look something up, that is a resource.
Can I use MCP without any Skills?
Yes. MCP alone gives the agent access to capabilities and many workflows stop there. Skills become useful when the same multi-step job has to be performed consistently, or when output quality needs to be predictable.