What is MCP? The Model Context Protocol, explained

What MCP is (and the problem it solves)

Large language models are powerful but isolated — they can't see your files, your database, or today's data unless something feeds it to them. Before MCP, every app wired each model to each tool with bespoke code that broke constantly. MCP standardizes that connection: a model speaks one protocol, and any MCP server on the other end offers a menu of tools and resources it can call. Think of it as a universal adapter between AI models and the world's tools.

• An open standard (introduced by Anthropic) for connecting AI models to tools and data
• One protocol instead of a custom integration per tool
• Works across MCP-compatible clients — Claude Desktop, IDEs, and agents

How an MCP server works

An MCP server advertises a set of tools (actions the model can invoke) and resources (data it can read). The client asks the server what's available, the model decides which tool to call to answer a request, the server runs it and returns the result, and the model uses that result in its reply — all over the standard protocol.

• Tools: callable actions, e.g. search a knowledge base or convert a URL to Markdown
• Resources: readable data the model can pull into context
• Transport: the client and server exchange JSON-RPC messages over the MCP standard

Why MCP matters for AI agents

MCP turns a chat model into an agent that can actually do things with your data. Because it's a standard, one MCP server works with every compatible client, and you're not locked into a single vendor's plugin format. For teams, it means your knowledge and tools are exposed once and reusable everywhere.

• Give a model live access to your documents, memory, and APIs
• Reuse one integration across every MCP-compatible client
• No vendor lock-in — it's an open protocol, not a proprietary plugin

Give your AI a knowledge base over MCP with Kit for AI

Kit for AI's MCP server exposes your knowledge bases, document conversion, memory, and web search as MCP tools. Point an MCP client at it and your model can convert a file, search your documents, remember a fact, or recall one — grounded in your data, on private local models. It's the fastest way to give Claude a persistent, cited knowledge base.

• Search your knowledge bases and get cited answers, straight from the client
• Convert documents and URLs to clean Markdown on demand
• Persistent memory: remember and recall facts across sessions
• One endpoint, secured by an API key — no custom server to build

FAQ

What does MCP stand for?

MCP stands for Model Context Protocol — an open standard for connecting AI models to external tools and data through one common interface.

What is an MCP server?

An MCP server exposes tools (actions) and resources (data) that an AI model can use over the protocol. Kit for AI runs an MCP server that gives models access to your knowledge bases, conversion, memory, and web search.

Is MCP only for Claude?

No. MCP is an open standard, so any MCP-compatible client can use an MCP server. Claude was the first major client, but the protocol is vendor-neutral.

How do I connect a knowledge base to my AI over MCP?

Create a Kit for AI API key, point your MCP client at the Kit for AI MCP endpoint, build a knowledge base, and your model can search it and answer with citations — no custom code.