MCP Server

A process that exposes tools, resources, or data through the Model Context Protocol. An MCP server advertises what it can do (its capabilities), and MCP-compatible AI clients can discover and invoke those capabilities. Servers can be local (running on your machine) or remote (accessible over a network).

Example: LlmsTxtKit runs as an MCP server that exposes tools like fetch-llmstxt (retrieve a site's llms.txt file), validate-llmstxt (check it against the spec), and generate-context (produce a structured summary for an AI agent). An agent connected to this server can use these tools without knowing anything about the llms.txt spec itself: the server handles the expertise.

Why it matters for writers: MCP servers are the building blocks of agent capabilities. Each server is a self-contained package of functionality with its own documentation needs: tool descriptions, configuration options, authentication requirements, error handling, usage examples. This is a rapidly growing documentation space with very few established patterns or best practices. If you're a technical writer looking for a niche that's both useful and uncrowded, this is it.

Related terms: Model Context Protocol · AI Agent · Tool Use · Schema