A standardised server that exposes tools, data, and prompts to LLMs over the Model Context Protocol — letting any MCP-compatible AI assistant interact with your systems.
An MCP server is a server implementation of the Model Context Protocol — Anthropic's open standard for giving language models structured access to tools, data sources, and prompt templates. Once you expose your data or capabilities through an MCP server, any MCP-compatible AI client (Claude Desktop, IDE integrations, agents) can use them through a uniform interface. MCP is to AI tools what USB-C is to peripherals.
Before MCP, every AI assistant integration required custom plumbing — different tool definitions, different auth patterns, different prompt structures for every client. MCP standardises that. For organisations with internal data and tools that should be accessible to AI assistants, building one MCP server replaces building N integrations. For SaaS vendors, exposing an MCP server makes the product reachable from every AI assistant on the market.
MCP is one of the most under-appreciated standards in AI right now. We have built MCP servers for internal developer tools (calendars, alarm systems, code search) and for production data integrations. The pattern that works: keep the MCP server thin and stateless, push business logic into the underlying systems it wraps, treat tool definitions as a public API contract that needs versioning, and instrument every tool call for cost and quality observability. The same orchestration discipline that applies to LLM calls applies to MCP-exposed tools.