Get products ready for AI search with GitHub Copilot
Getting products ready for AI search with GitHub Copilot means using agent mode in VS Code to read a product's StoreSEO GEO score, decide on product schema, and apply the FAQs and AI snippet you approve, with the editor confirming each tool call.
Last updated: October 2026
Set up GitHub Copilot for StoreSEO
Skip this if GitHub Copilot is already connected. The full guide, with the alternatives, is on the GitHub Copilot page.
- 1
Add StoreSEO to .vscode/mcp.json
Create or open .vscode/mcp.json in your workspace and paste this. VS Code uses a top-level servers key, not mcpServers, and a remote server needs type http.
JSON{ "servers": { "storeseo": { "type": "http", "url": "https://mcp.storeseo.com/mcp" } } } - 2
Start the server and sign in
Run MCP: List Servers from the Command Palette, pick storeseo and start it. If it asks you to sign in, pick your Shopify store in the browser and approve access. Then open Copilot Chat in Agent mode, check the tools icon lists StoreSEO and ask this.
PromptUse StoreSEO to show me my store's SEO score breakdown.
How does this work in GitHub Copilot?
You open the Copilot Chat view in VS Code, switch to agent mode, and the storeseo server from .vscode/mcp.json is listed among its tools. You type: why is the Merino Beanie weak for AI search, and what can StoreSEO fix. Copilot calls storeseo_start and storeseo_get_resource_seo, and the geo block in the result tells it which AI-readiness criteria fail. Because you are already in the theme repository, you can also ask Copilot to look at how the theme prints Product JSON-LD, so you decide with both views whether to enable StoreSEO's product schema.
VS Code puts a confirmation card in front of each tool call that is not a plain read, showing the tool name and its arguments, and that card is separate from the yes you give in chat. For this job the cards you will see are storeseo_update_schema_settings, storeseo_apply_resource_optimization, and, for a thin description, storeseo_write_product_description. Read the arguments on each. A schema change is shop-wide, so it affects every product, and a description write replaces the live text with no undo. The preview, storeseo_preview_resource_optimization, writes nothing but spends AI credit.
The usual order is read, decide on schema, preview, apply. The apply returns the re-analysed checklist, so Copilot can list what now passes and what still needs you, for example a product category or barcode that only Shopify admin or the app can change. If the server was added through a workspace file committed to the repository, remember teammates share that file, so keep tokens out of it and let each person sign in with OAuth.
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You: Why is the Merino Beanie weak for AI search, and what can StoreSEO fix?
- storeseo_start read-only
- storeseo_get_resource_seo read-only
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GitHub Copilot: GEO is 41. Product schema is off, and there are no FAQs or snippet. Enabling schema is shop-wide. Turn it on for the whole store?
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You: Yes, enable it.
- storeseo_update_schema_settings needs approval
- storeseo_preview_resource_optimization preview
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GitHub Copilot: Preview is ready: five FAQs and a snippet, projected GEO 69. Say apply and confirm the VS Code prompt.
What to ask GitHub Copilot
@workspace Use StoreSEO to read the GEO checklist for the Merino Beanie and list what an AI shopping agent cannot find. Do not change anything.
Check whether product schema is enabled in StoreSEO and compare it with the JSON-LD in this theme before I turn it on.
Preview FAQs and an AI snippet for the Merino Beanie, show the projected GEO score, and wait for my confirmation before applying.
- Which of my products have the lowest GEO score, and what is missing for AI shopping agents?
- Make the product Merino Beanie ready for AI search: FAQs, AI snippet and product schema. Preview first.
- Scan the description of my best seller for AI agents and ask me the questions it needs.
- Rewrite the description of Ceramic Pour Over from my answers. Keep a copy of the old one for me.
- Is product JSON-LD schema enabled on my store? If not, explain what turning it on changes.
What StoreSEO does: ai search readiness
GEO is StoreSEO's AI readiness score for products. The agent reads which GEO criteria fail, fixes the ones a tool can fix (FAQs, AI snippet, alt text, product schema), and can rewrite a thin description from your own answers to StoreSEO's questions.
Requires: FAQs, AI snippets and descriptions spend AI Content Optimizer credit. The product needs a focus keyword, set in the StoreSEO app, before a description scan or rewrite.
- 1
Read the GEO checklist
The agent reads the product's GEO block: the score and every AI-readiness criterion that passes or fails.
- 2
Turn on product schema if it is off
Product JSON-LD is a shop-wide setting, so enabling it clears that criterion for every product at once. If you then decide not to apply the rest, the agent switches back off only the schema it turned on.
- 3
Preview FAQs and the AI snippet
The preview generates FAQs and an AI snippet (summary, benefits, best for) and projects the new SEO and GEO scores without saving.
- 4
Scan the description
For a thin or missing description, StoreSEO scores it on seven pillars (identity, materials, dimensions, features, use cases, what is included, care) and returns questions. The agent asks you each one, word for word.
- 5
Write and apply
With your answers, StoreSEO writes the description and saves it immediately; the response holds the only copy of the old text. The previewed FAQs and snippet are applied after your yes.
AI search readiness reference
| Scope | Products only; collections, pages and articles have no GEO score |
|---|---|
| Fixable by tools | FAQs, AI snippet, image alt text, product schema, description |
| Fixed only in the app or admin | Product title, category, product type, image count, inventory, variant barcode, SKU, price, image |
| Description pillars | Identity, materials, dimensions, features, use cases, what is included, care |
| Description write | Saved immediately to Shopify and StoreSEO; no undo and no revision history |
| Old description | Returned once in the write response, the only remaining copy |
| Product schema | Shop-wide toggle; credits the schema criterion on every product |
| Prerequisite | A focus keyword on the product, set in the StoreSEO app |
Rules GitHub Copilot follows
- The scan's questions go to you word for word and in order; the agent does not answer them for you.
- A description is only written without questions when you decline to answer or authorize a bulk run without them.
- Writing a description replaces the current one at once with no undo, so the agent asks first and keeps the old text the response returns.
- If the agent enabled product schema for this flow and you stop before applying, it turns that schema back off; it never disables a schema you already had on.
- Criteria only you can fix get one link to the product's fix page, not a link per criterion.
In GitHub Copilot
VS Code uses the servers key in .vscode/mcp.json, while mcpServers belongs to the portable .mcp.json at the project root, so a Cursor or Claude snippet pasted unchanged will not work. On Copilot Business and Enterprise an organization admin must enable MCP servers in Copilot policy. Keep the apply, schema and description-write tools on VS Code's confirmation prompt, because StoreSEO asks for your yes in the chat and the editor's confirmation is the hard stop. A .vscode/mcp.json committed to the repository is shared with your team.
What runs without asking. Reads such as SEO scores, store listings, settings and Google reports run straight away. Generating a preview spends AI credit but writes nothing, and StoreSEO tells the agent to say what a generation will cost before it runs one. Applying content, optimizing images, changing settings, publishing llms.txt or agents.md, writing a product description and deleting anything wait for your yes in the conversation. That yes is an instruction the agent follows, not a lock on the server, so your client's own tool-approval setting is the hard stop.
Questions
Does Copilot agent mode confirm StoreSEO writes in VS Code?
VS Code shows a confirmation for tool calls that go beyond reads, with the tool name and arguments, unless you allowed that tool. StoreSEO also tells the agent to wait for your yes in chat, and the editor prompt is the hard stop.
Can Copilot check my theme before turning on StoreSEO product schema?
Yes. Copilot can read your theme files and StoreSEO reports whether product schema is enabled, so you can compare them before the shop-wide switch. Spotting a duplicate Product block is the agent's own work, not a StoreSEO check.
What is a GEO score in StoreSEO?
GEO is StoreSEO's AI readiness score for products. It measures how well a product can be understood by AI shopping agents and generative search, using criteria such as FAQs, an AI snippet, image alt text, product schema and the quality of the description.
Can I undo a rewritten product description?
Not inside StoreSEO. The new description is saved immediately and StoreSEO keeps no revision history. The response returns the previous description once, so ask the agent to keep it for you before it writes.
Why does the agent ask me questions before writing a description?
StoreSEO scans the description on seven pillars and returns questions for the facts it cannot infer, such as materials or what is in the box. Your answers become stated facts in the new copy instead of guesses.
Does enabling product schema affect every product?
Yes. Product JSON-LD is a shop-wide setting, so turning it on clears that criterion for every product at once, and turning it off removes it everywhere.
Keep going
AI search readiness with other agents
More GitHub Copilot guides