What AI assistants can do

Connect an AI assistant like Claude or ChatGPT to our MCP server and ask it to do real work on a store’s catalog: check which vehicles a product fits, add or remove fitment, pull a coverage report, export a filtered CSV, or fix the words shoppers search for but the catalog doesn’t use.

What you can ask for today

I want to…	Ask something like	Section
See what vehicles a product fits	”What does SKU 24-186766 fit?”	Check and fix vehicle fitment
Add missing vehicles to a product	”Add 2018-2021 Jeep Wrangler to SKU 24-186766”	Check and fix vehicle fitment
Remove wrong vehicles from a product	”Remove all F-150 fitments from SKU 24-186766”	Check and fix vehicle fitment
Know how good my fitment data is	”What’s my fitment coverage for Bilstein?”	Measure fitment coverage
Get a spreadsheet of products	”Export all products with no fitment data”	Export your data
List every make and model in my catalog	”Export all makes and models we cover”	Export your data
Fix search results for a term	”Shoppers search ‘tpms’ but get nothing, fix it”	Manage synonyms

Check and fix vehicle fitment

Read the vehicles a product fits, check whether a vehicle exists in the fitment data, and add or remove fitments. Useful for a supplier’s updated application list, a customer asking “does this fit my truck?”, or a product showing No Fitment Data that shouldn’t.

What vehicles does SKU 24-186766 fit?

Add 2018 through 2021 Jeep Wrangler Rubicon to SKU 24-186766.

Here's an application list from our supplier. Add all of these to product 7823419023.
[paste the list]

What you get back. For a lookup: the product’s fitment type (Vehicle Specific, Universal Fit, No Fitment Data, Non-Vehicle Products, or Many Fitments) and its vehicles, with consecutive years grouped into ranges like 2018 - 2020. For a write: how many fitments were added. Vehicles the product already had are skipped.

Good to know:

Identify the product by product ID, SKU, or URL handle (Shopify only). Use one of the three, not several. SKU lookup isn’t available on every platform, and a SKU matching more than one product returns an error. Use the product ID in both cases.
2018 - 2021 is expanded into one fitment per year.
Vehicles are checked against the fitment data first. If any vehicle in the request isn’t found, nothing is added, and the assistant shows the valid values to pick from. A vehicle that isn’t in the data yet can still be added once you confirm it.
A year range is checked year by year, so every year in it must exist in the data.
Ask for the valid values of a field to check spelling, such as “which models are there for a 2020 Ford?”
Additions show up immediately when you ask about the product again. Shoppers see them after the next index rebuild.

Removing fitments

Remove fitments from a product, one product at a time, identified the same way as above.

Remove all F-150 fitments from SKU 24-186766.

Take 2019 and 2020 off the Jeep Wrangler fitments on product 7823419023.

Clear all fitment data from SKU 24-186766.

Good to know:

You describe what to remove as a pattern, not an exact row. A field you leave out matches any value, so “remove the F-150 fitments” removes every F-150 the product has, whatever the year or submodel. Ask to see the product’s fitments first if you aren’t sure how wide that reaches.
Years are split, not dropped whole. Taking 2019 - 2020 out of a 2018 - 2022 fitment leaves 2018 and 2021 - 2022.
Fitments that came from an external feed can be removed too, not just ones added in the editor.
Clearing a product’s fitment data entirely shows you a preview first and needs an explicit confirmation.
A pattern that matches nothing removes nothing and tells you so, rather than failing quietly.
Removals are recorded in Fitment Operation History, tagged MCP with your email.

Measure fitment coverage

How much of the catalog has usable fitment data, either across everything or scoped to a vendor, category, price band, or search query.

How's our fitment coverage?

What's the fitment coverage for Bilstein products?

Compare fitment coverage for Bilstein and KYB.

What you get back. Total product count, a breakdown by fitment type with counts and percentages, and an overall coverage percentage. The numbers come back in the conversation rather than as a file, so follow-up questions work.

Good to know:

Vehicle Specific, Universal Fit, and Many Fitments all count as covered. Non-vehicle products count toward the total but not as covered, so they lower the percentage.
Requires fitment classification to be configured for the store.
Scope it by naming the vendor or category you want. The assistant has no sales data, so it can’t work out which brands matter most on its own.
For coverage as a table broken down by vendor, ask for an export instead.

Export your data

A download link for a CSV of products, of fitment values (every make, model, and year covered), or a coverage pivot table.

Export every product with no fitment data.

Export all products from Bilstein under $200.

Export a table of fitment status broken down by vendor.

What you get back. A download link, and for product exports the number of products matched. If the filters match nothing, you get the values that do exist for the fields you filtered on, so a near-miss like “Bilstien” is easy to correct.

Good to know:

Treat the link as a password. It carries the store’s export credential, so don’t post it anywhere public.
Product CSVs have one row per product and per fitment and per variant, so the file is larger than the product count suggests.
Fitment exports nest fields in the order you ask for them. Makes then models gives every make with its models.
A pivot table needs a row field and a column field. “Fitment status by vendor” gives vendor rows and fitment-status columns.

Manage synonyms

The sets of words search treats as equivalent, so a shopper searching tpms also finds products described as tire pressure sensor. Groups can also carry exclusions, for when a term pulls in products that don’t belong.

Do we have a synonym for "tpms"?

Shoppers searching "tpms" get nothing. Set up a synonym with "tire pressure sensor" and "tire pressure monitoring sensor".

Searching "wheel" brings back steering wheels. Can we exclude those?

What you get back. The matching groups with their terms and exclusions, or a confirmation of your edit plus any warnings.

Good to know:

Many stores inherit a shared synonym list. Editing requires a store-specific copy first, either copying what is inherited or starting empty. Going back to the inherited list discards those changes and asks you to confirm.
Write terms as plain words. Multi-word terms like brake pads need no quotes; a quoted term only matches when a shopper searches with quotes.
Exclusions only apply when the query matches the group’s first term, so put the term you’re fixing first. They also require the negative-synonyms feature, and you get a warning if it isn’t enabled for the store.
Edits can be validated without saving, and deletions show you the group before removing it.

Getting good results

Name products precisely. A SKU or product ID beats a description.
Paste raw data. Supplier lists don’t need reformatting first.
Ask follow-ups. The data stays in the conversation: “now break that down by vendor”.

What it can and can’t do

Scoped to one store, the single store whose server URL you connected.
It reads catalog and fitment data. It has no access to orders, sales, or revenue, so it can’t rank or prioritize products and brands by how they perform.
It can write vehicle fitments and synonym groups. Nothing else: not products, prices, inventory, search configuration, the Convermax account, or the ecommerce platform’s admin.
Fitments are edited one product at a time. Bulk changes across many products still belong in the Fitment Editor.
One unknown vehicle blocks the whole add. A vehicle you confirm is added whether or not it exists in the data, so skim large pasted lists.
Synonym deletions take a second confirmation and show you the group first.
Fitment changes reach shoppers at the next index rebuild, not immediately.
Export links carry a credential. Anyone with the link can download that data.

Review and revoke connected apps from the AI Tools page in the Convermax app. See Managing connected apps.

What’s next

We’re expanding what AI assistants can do with a store.

Have a workflow you’d like to hand off to an assistant? Tell us at [email protected].