MCP (Model Context Protocol): what it means for LLM agents

For years everyone's been wiring up their own integrations for LLM agents: this tool, that DB, that billing pipe. Every project starts over. MCP solves this — a client/server protocol where agents see tools and data through a single interface.

Why it's picking up

• USB-C for tool-use: one protocol, anywhere.
• No vendor lock — OpenAI, Anthropic, local models all call the same servers.
• Auditable: every tool-call becomes loggable and explainable.
• Security: clean enforcement points at the client/server boundary.

How we use it

New client projects start MCP-native. We expose internal tools (retrieval, DB queries, CRM calls) as MCP servers, and the agent client can be anything. Big upside: swap the LLM provider later without rewriting the tool layer.

When not to bother

If your agent just calls a prompt and doesn't touch anything else, MCP is overkill — a REST call is simpler. Once you have 3+ tool interactions, the switch pays for itself.

Takeaway

Starting a new AI agent in 2026? Go MCP-first. Already have something running? Converting the tool layer is worth the next major release — not an emergency, but a clear direction. Happy to help you migrate.