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's distribution, the same way an API was ten years ago.
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 half. Designing tools an AI model uses correctly is the craft, and it's where most MCP servers fall short.
- 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 we actually get
Short answers, no sales language. If yours isn't here, ask an engineer directly.
Ask us anythingWhat 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, every compatible assistant can use it.
Why would our SaaS want one?
Because your customers increasingly work inside AI assistants, and products reachable from there get used more and churn less. Whoever shows up in that surface first tends to keep the seat.
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.
Want your product inside AI assistants?
Tell us what your product does. We reply with what its MCP server would look like.