MCP servers

Make your product usable from inside Claude, ChatGPT, and AI coding tools. One server, every compatible assistant.

Your customers are moving their work into AI assistants. An MCP server puts your product there with them: they can ask an assistant to pull a report, create a record, or check status in your app without opening a browser tab. For a SaaS, that is a new way for customers to reach the product, much like a public API.

Your API as MCP tools

We map your product's capabilities to well-designed MCP tools, so AI assistants can search, create, and update on a user's behalf.

Auth done properly

OAuth flows, scoped tokens, and per-user permissions. An assistant acting for a user can do exactly what that user could, and nothing more.

Hosted and monitored

A remote MCP server your customers connect to in minutes, deployed on your infrastructure or ours, with logging and usage visibility.

Docs and listing

Connection guides for your users and the metadata AI clients need to discover and describe your tools correctly.

What makes MCP tools good

Exposing an API is the easy part. The harder part is designing tools that a model uses correctly.

A few well-named tools instead of one tool per API endpoint
Descriptions written for the model: when to call it, not just what it does
Outputs sized for a context window, with pagination where lists get long
Least-privilege scopes per user, enforced server-side
Confirmation steps on destructive operations
Logs of every tool call, so you can see how assistants use your product

Questions clients ask

Short answers, no sales language. If yours isn't here, ask an engineer directly.

Ask us anything

What is MCP in plain terms?

The Model Context Protocol is an open standard, started by Anthropic and now adopted across the industry, that lets AI assistants connect to outside products and data. An MCP server is the adapter that makes your product one of the things assistants can use.

Which AI tools can connect to an MCP server?

Claude, ChatGPT, and most AI coding tools including Cursor and Claude Code support MCP, and the list keeps growing. You build one server, and every compatible assistant can use it.

Why would our SaaS want one?

Your customers already do some of their work inside AI assistants. An MCP server lets them use your product from there without opening it in a browser.

Is it safe to let AI touch our API?

The server only exposes the tools you choose, each scoped to what the authenticated user may do. Destructive operations can require confirmation. The assistant never holds your credentials; the MCP server brokers every call.

Why not just give the AI our REST API?

An assistant can call a REST API, but most APIs are built for programmers, not models. The assistant has to guess which endpoints matter and how to sign in. An MCP server gives it a short list of clear tools, handles sign-in for each user, and limits what each tool can do. Claude, ChatGPT and other MCP clients can connect to it without custom code on their side.

How much does an MCP server cost and how long does it take?

It depends on how many tools the server exposes and how your sign-in works, so we do not publish a project total. We bill $30 an hour, or by milestone. For milestone work, we read your API, agree on the tool list in a written scope, and split it into milestones. A clearly scoped milestone can have a fixed price. Each milestone ends with tools you can try in a real AI assistant before you accept and pay.

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Want your product inside AI assistants?

Tell us what your product does. We reply with what its MCP server would look like.

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