Question 1

What is the Model Context Protocol (MCP)?

Accepted Answer

MCP is an open protocol that lets AI clients connect to external tools and data via MCP servers, standardizing how models request resources, run tools, and receive results.

Question 2

How do MCP servers and clients work?

Accepted Answer

An MCP client (e.g., an AI app) connects to one or more MCP servers. Servers expose tools, resources, and prompts over a standard interface; the client invokes them and streams results back to the model.

Question 3

How do I connect an MCP client?

Accepted Answer

Install or configure an MCP-compatible client, add your server config (executable or URL plus environment variables), then restart the client to discover and use the server's tools and resources.

Question 4

Is MCP open-source?

Accepted Answer

The protocol is open and community-driven with many open-source servers. You can host servers locally or deploy them remotely.

Question 5

MCP vs plugins or custom integrations?

Accepted Answer

Unlike bespoke plugins, MCP standardizes capabilities (tools/resources/prompts), making integrations reusable across clients and easier to maintain.

Question 6

What about security and permissions?

Accepted Answer

Servers run separately from the client and expose only what you configure. Access to external APIs or files is scoped by the server implementation and environment.

Question 7

Does MCP cost anything?

Accepted Answer

MCP itself is free; costs depend on your LLM provider and any external APIs your servers call.

Question 8

How do I get started?

Accepted Answer

Pick an MCP client, choose or build a server, configure credentials, and test with a simple tool call. See modelcontextprotocol.io for the spec and examples.

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