If you manage Quotivity, a fair amount of your day is probably spent doing things that feel like they should take five seconds but don't. Cloning a price book and adjusting margins across forty SKUs. Auditing compatibility rules for a new product line. Building out a bundle option structure from a spec someone sent in Slack. Useful work, but slow.
We built the Quotivity MCP server to change that.
MCP stands for Model Context Protocol, an open standard that lets AI assistants connect directly to external tools and APIs. Think of it as a secure handshake between an AI (like Claude or ChatGPT) and a piece of software (like Quotivity), giving the AI permission to read and write real data on your behalf.
Without an MCP connection, an AI can only help you describe what you want to do. With one, it can actually do it.
For admins, that distinction matters a lot. Instead of asking an AI to explain how to configure a compatibility rule, you can ask it to draft the rule from plain language, check it for conflicts against your existing rules, preview how it affects your bundles, and create it. All in one conversation.
The server exposes most of the Quotivity admin surface. Here is what you can work with through an MCP-enabled AI today.
Bundles. Create, update, activate, or deactivate bundles. Manage options and the products inside them. If you are standing up a new product line or restructuring an existing one, you can do it conversationally.
Price books. Create price books, set product prices, clone an existing book, and query which price books contain a given product. Good for standing up regional pricing or customer-segment tiers without having to click through every row.
Compatibility rules. This one is worth calling out. You can draft a compatibility rule from plain language (the same AI flow in the admin UI), check it for conflicts against your current rule set before saving, preview how a rule change would affect bundle selections across your catalog, and then create the final rule. The conflict detection and impact preview steps mean less breakage when you push changes to production.
Calculated prices and quote rules. Full create, read, update, and delete access. Same for dynamic property sets and roll-ups.
HubSpot properties. Read object schemas, search products, and batch-create, update, or delete CRM property definitions. The property write tools require connecting the HubSpot MCP Auth App (one OAuth flow, runs once per user).
Account metadata and feature flags. Useful when you are scripting or building on top of the API and need to check what is enabled before running an operation.
First, make sure you're signed into Quotivity Studio at app.secure.quotivity.com (or app.secure-eu1.quotivity.com for our EU-hosted customers). If you haven't signed in, you'll get an "Unauthorized" message.
The server runs at mcp.secure.quotivity.com (or mcp.secure-eu1.quotivity.com). Your existing Quotivity session handles authorization, so there is no separate credential to manage.
If you are a HubSpot partner managing Quotivity for clients, this opens up a few things. You can audit a client's rule set and surface conflicts before a call. You can draft compatibility rules from a product spec and have something real to review rather than building blind. And for repetitive catalog or pricing work, an MCP-connected AI cuts the time considerably.
It also means your team members who are less deep in the Quotivity admin UI can do more, since they can work through the AI instead of learning every configuration surface directly.
If you run into anything during setup, the troubleshooting section of this KB article covers the common errors, and Quotivity support is available if something does not resolve.