Shopline MCP. Automate your store operations from natural chat.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Shopline MCP Server lets your AI agent run as a full-time store operations manager. It handles everything from auditing product inventory and checking low stock counts to pulling customer profiles and compiling order fulfillment lists using direct API calls, all through natural conversation.
What your AI agents can do
Get order details
Retrieves all transactional data for one specified order ID.
Get product details
Fetches the full listing details and variant information for a single product SKU.
Get shop info
Retrieves high-level metadata, such as currency settings or overall store status.
The agent lists all available products using list_products or checks specific item details via get_product_details.
You query the store for customer records using list_customers to analyze demographics and account status.
The system lists all recent orders with list_orders, allowing you to review transaction dates, totals, and item counts.
You pinpoint a single order ID and run get_order_details to retrieve every piece of data associated with that specific transaction.
The agent lists all product groupings available using list_collections, helping you understand how your products are categorized.
You fetch general store information and metadata by calling get_shop_info.
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Supported MCP Clients
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Shopline MCP Server: 7 Tools for E-commerce Data Management
These seven tools allow your AI agent to execute specific read operations across the entire Shopline data model—from individual products to global store settings.
019d7607get order details
Retrieves all transactional data for one specified order ID.
019d7607get product details
Fetches the full listing details and variant information for a single product SKU.
019d7607get shop info
Retrieves high-level metadata, such as currency settings or overall store status.
019d7607list collections
Lists every product grouping (collection) currently active in the storefront.
019d7607list customers
Returns a list of all registered customer accounts and basic profile information.
019d7607list orders
Lists multiple recent orders, providing summaries of transactions across a date range or limit.
019d7607list products
Returns an index of every product in the shopline catalog.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Shopline, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
The Shopline MCP gives your AI agent full administrative access to your store's backend data. It lets your agent act like a dedicated operations manager that never logs into the vendor panel—it just talks directly to your Admin API, giving you immediate read access to critical business functions through simple conversations.
- Audit Product Catalog: You can list every single product in the catalog using
list_products. If you need specifics on one item, useget_product_detailsto pull all the listing details and variant info for a specific SKU. To see how your products are grouped, runlist_collections, which lists every active product grouping. You can also check out general store information and metadata by callingget_shop_info, which returns things like currency settings or overall store status. - Track Customer Activity: Your agent pulls customer records using
list_customers. This gives you a list of all registered accounts and basic profile info, letting you analyze demographics and account status at a glance. - View Order History & Details: To audit live sales pipelines, the system lists multiple recent orders with
list_orders, giving summaries across a date range or specific limit for transaction dates, totals, and item counts. If you need every piece of data associated with one sale, you pinpoint a single order ID and runget_order_detailsto retrieve all transactional information.
When your agent has access to these tools, it handles complex queries immediately. For instance, if you ask it to look at the last ten orders and then check stock levels for products in the 'Dog Collar' collection, it runs those specific API calls—list_orders, get_product_details, and list_collections—and spits out one single answer.
You don't have to jump through menus or build complex reports; your agent just talks to the data source directly.
How Shopline MCP Works
- 1 Anchor the Shopline MCP interface directly into your agent's framework.
- 2 Securely place your
SHOPLINE_ACCESS_TOKENmatrix within the workspace to lock down access boundaries. - 3 Prompt your agent with a natural language query (e.g., "What were the total sales from last Tuesday?") and let it run the required tools.
The bottom line is: you give the agent a question, and it figures out which of the seven available tools it needs to use to answer it for you.
Who Is Shopline MCP For?
This is for e-commerce operations teams who live in dashboards. If you're tired of having to copy-paste data between the order management system, the inventory tracker, and a separate customer CRM just to answer one question, this is for you.
They use list_orders and get_order_details together to audit fulfillment bottlenecks and verify which orders are stuck in payment processing.
They run list_products combined with list_collections to check if new seasonal inventory is properly categorized and visible across the entire store structure.
They use list_customers and get_product_details to quickly pull a client's profile history and cross-reference which specific, high-value products they bought previously.
What Changes When You Connect
- Audit entire order pipelines instantly. Instead of running separate reports, use
list_ordersto get a summary list and then drill into individual purchases withget_order_details. You see the total value and item breakdown in one pass. - Manage inventory without logging in. Use
list_productsto see everything listed, and then callget_product_detailson any SKU you're concerned about to verify exact stock counts or variant availability. - Analyze customer behavior easily. Run
list_customersto get a roster of buyers. You can combine this with product data to identify your top-spending client segments quickly. - Verify store settings in seconds. The
get_shop_infotool pulls core metadata, letting you confirm things like the current operating currency or tax status without navigating deep into the admin console. - Map out product structure efficiently. You can use
list_collectionsto map your entire site hierarchy and then cross-reference that withlist_productsto ensure no orphaned items exist.
Real-World Use Cases
Investigating a high-value return.
A customer service rep needs to know what was bought, when it arrived, and how much they spent. The agent runs get_order_details using the order ID, which immediately gives the full item list, total cost, and purchase date—all without leaving the chat window.
Checking for seasonal stock issues.
Merchandising needs to know if the new fall line is ready. They ask the agent to run list_products then filter by keywords, followed by get_product_details on the top 5 candidates to confirm inventory levels.
Auditing a sales day's revenue.
A manager needs a quick snapshot of last week's activity. They ask the agent to run list_orders, specifying the date range, and the agent returns an aggregated list summarizing total value across dozens of transactions.
Finding out who bought similar items.
The marketing team wants to find VIPs. They ask the agent to run list_customers and then use that output as a filter parameter when calling get_product_details for top-selling products.
The Tradeoffs
Trying to get everything in one query.
Asking the agent: "Show me all orders, and also list customers who bought product X, and tell me what the store's currency is."
→
Break it down. First, ask for list_orders with a date range. Then, run get_product_details for Product X. Finally, call get_shop_info to get the currency. This uses multiple targeted tools and gets better data.
Forgetting to specify an ID.
Asking: "Tell me about that order."
→
You must provide the necessary identifier. The agent needs a specific ID for get_order_details(order_id='12345') or get_product_details(sku='XYZ'). No ID means no data.
Confusing products and collections.
Asking: "List the category 'Winter Gear' orders."
→
Use list_collections first to find the correct collection slug. Then, use that slug in your prompt when asking for order data via list_orders or get_order_details.
When It Fits, When It Doesn't
Use this MCP Server if your goal is reading operational data: auditing sales, checking inventory levels, viewing customer profiles. You should use it whenever you need the agent to query read-only information from the Shopline backend.
Don't use this if you need to write or modify data (e.g., change a price, mark an order as shipped, update a description). For those tasks, you'll need a different type of API integration that grants write permissions and executes actions.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Shopline. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 7 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Managing e-commerce backend data usually means switching tabs until your eyes bleed.
Today, answering a simple question like, 'Are we running low on the Deluxe Dog Collar?' requires logging into the admin panel. Then you navigate to Inventory > Products. You search for the SKU. If that doesn't work, you check the Collections tab. Finally, you might run a separate report to see recent sales velocity.
With this MCP server, you just ask your agent: 'Check the stock on the Deluxe Dog Collar.' It runs `get_product_details` and gives you the precise count immediately. No tabs, no searching, just the answer.
Shopline MCP Server: Get immediate data access to orders and products.
You don't have to open three different reports—one for collections, one for customers, and one for sales. The agent runs `list_orders` (for sales) and can cross-reference that with the customer data from `list_customers`. It ties it all together in a single response.
It’s not just about getting the data; it's about having your AI client process seven different API calls into one cohesive, understandable answer. That saves time.
Common Questions About Shopline MCP
How do I check product stock using get_product_details? +
The get_product_details tool returns the current inventory count and details for all associated variants of a specific SKU. This is your primary source for real-time stock checks.
Can list_orders show me more than just the total amount? +
Yes, list_orders provides an aggregated summary of transactions across the date range you specify. You can then use get_order_details to get item-level breakdowns for individual orders.
Does list_customers give me enough data to analyze demographics? +
list_customers provides basic profile information and status flags. While it doesn't run complex demographic reports, it gives you the raw data set needed to start that analysis.
How do I list all products in my store using list_products? +
Simply call list_products. This tool returns an index of every product SKU currently registered with Shopline, giving you a full catalog overview.
When I use `get_order_details`, what specific information does it pull for a single transaction? +
It retrieves detailed line items, payment status, and shipping addresses for one order ID. You get the full breakdown of products purchased, including SKUs and quantities, plus when the order was placed.
What is the best way to use `list_collections` to find product groupings? +
The tool lists all active collection names and their associated IDs. This lets you see what groups of products exist in your store, acting as a directory for curated inventory.
If I run `list_orders`, how do I handle rate limits or API errors? +
The agent will typically throw an error if the limit is hit. You just need to implement simple backoff logic in your client code; retrying after a short delay usually fixes it.
When setting up the MCP, how do I securely manage my Shopline access tokens? +
The system expects you to anchor the SHOPLINE_ACCESS_TOKEN as an environment variable. Always keep this token locked down in your workspace; it's necessary for any tool function.
Can the AI forcefully transition or edit an order status directly? +
Currently, the integration specifically implements reading mechanisms (list_orders, get_order_details) as a query matrix tailored explicitly around monitoring and auditing. It does not actively expose a write mutation structurally to alter or destroy existing operational orders.
Why do I need a Custom Admin API integration token and not a public one? +
Because the Admin API is the unadulterated backend context designed primarily for secure backend logic rather than client storefront interfaces. This token permits your integration to run system-level monitoring, extraction over raw orders, and sensitive customer profiles natively.
Is this tool accessing the Shopline GraphQL portal or REST architecture limitlessly? +
By structural intent, we implement targeted endpoints using Shopline's scalable endpoints to parse specifically filtered responses like single pagination segments to avoid massive latency. You interact efficiently bypassing raw structural limits naturally via these curated list_x and get_x procedures.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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