What is MCP and when does it make sense for my company?
Model Context Protocol (MCP) is an open standard for connecting AI tools to data sources and functions. Instead of writing a custom integration per AI app (Claude integration, ChatGPT integration), you write one MCP server and all MCP clients can use it. For SMB it matters most when you run multiple AI tools side by side or want tooling reuse.
Try this first
- 1Understand the two sides: an MCP server (yours or off-the-shelf, e.g. GitHub, Slack, Postgres) exposes tools, resources and prompts. An MCP client (Claude Desktop, Cursor, IDE plugins) connects to it.
- 2Start with existing servers. The community has dozens for popular systems. Try wiring one into Claude Desktop, for example the filesystem server, to feel the UX.
- 3Build your own MCP server only if you have a specific internal API that multiple AI tools must reach. For a single tool, a regular API integration is often simpler.
- 4Mind permissions: an MCP server gives the AI client access to what the server exposes. Put the server behind auth and only expose the minimum tool set needed.
- 5Watch the ecosystem. MCP is young and moves fast: the spec, security model and tooling are still shifting. Pick stable dependencies and pin versions.
When to bring us in
Want to know if MCP fits now or a regular API integration is smarter at your scale, we can decide it together.
See also
- Can I paste a customer file or email into ChatGPT?Depends on the account and settings. Free ChatGPT and a Team tenant behave very differently from what most people assume.
- I want a one-page AI policy for my teamA real one-pager beats a thick document nobody reads. Four headers and concrete examples.
- How do I tell if an AI answer is made up?Models sound confident even when they are wrong. A few habits catch most mistakes.
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