Klevu (E-commerce AI Search) MCP. Master product discovery and merchandising logic.
Klevu AI Search MCP powers your e-commerce product discovery using natural conversation. Ask your agent to perform complex searches, audit category layouts, or fetch specific recommendations just by talking to it. You can execute keyword lookups, apply precise facet filters (like brand or size), and monitor global trending items without writing a single API call.
Give Claude and any AI agent real-world access
Find product listings across your entire catalog using natural language keywords.
Narrow down large result sets by applying specific characteristics like color, size, or brand.
Retrieve products configured for a specific category path to audit how your site displays content.
Fetch machine learning-driven suggestions, such as items frequently bought together or visually similar goods.
View the most relevant and fastest-selling products across your store to spot market opportunities.
Execute deeply nested, specific API queries using raw JSON structures.
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What AI agents can do with Klevu (E-commerce AI Search) - 10 Tools
These tools allow you to run every kind of search needed for an e-commerce site, from simple keyword lookups to complex JSON payloads.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Klevu (E-commerce AI Search) MCPSearch Autocomplete
Provides instant suggestions for users as they begin typing into a search bar.
Search Category
Retrieves product listings specifically configured for a given category page...
Search Filtered
Narrows down the catalog results by applying multiple specific criteria like color...
Search Keyword
Searches the entire product catalog using a general keyword provided in plain text.
Search Pagination
Gets chunks of search results when you need to view more items on long result pages.
Search Product Id
Fetches the complete details for a single product using its unique catalog ID number.
Search Raw
Allows you to send custom, complex JSON payloads directly against the Klevu API endpoints.
Search Recs
Retrieves product suggestions based on machine learning models that predict what...
Search Sorted
Performs a keyword search but allows you to specify how the results should be...
Search Trending
Shows the currently most popular and relevant products across your entire store.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
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 each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Klevu (E-commerce AI Search), then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Klevu. 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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Cloud Hosted
Managed infra
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Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on each call
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EU data residency
Token Compression
~60% cost reduction
The Headache of Testing Search Paths
Right now, testing product discovery feels like running an elaborate series of manual clicks or spending hours in Postman. You have to build one query for keywords, another payload just to filter by color, and then a third one just to check the category merchandising rules. It’s repetitive, slow, and frankly, it makes you hate your job.
With this MCP, that entire process disappears. You tell your agent what you want—for example, 'Show me all running shoes available in red.' The system executes multiple underlying calls (keyword search + facet filter) and hands you a clean list of results immediately. It’s not just faster; it's smarter.
Search & Discovery Tools
You don't have to write code or manage multiple API keys to check if a category page is displaying items correctly. You simply ask the agent, 'Check the Home Decor section for trending vases.' The system uses `search_category` and `search_trending` automatically.
The difference now isn't just speed; it’s scope. Your AI client acts as an expert e-commerce consultant, allowing you to audit merchandising rules, test recommendation logic, and monitor market trends without ever touching a developer console.
What Klevu (E-commerce AI Search) MCP does for your AI
Connecting Klevu through this MCP lets you treat your e-commerce catalog like a conversation. Instead of building complex JSON payloads in Postman or digging through developer documentation, you talk to your agent about what you need—whether it's finding every jacket under $100, checking if a specific category page displays related items correctly, or seeing what products are currently spiking in popularity across the whole store.
It takes search logic and merchandising rules out of the code and into plain English. This level of control means you can quickly audit product rankings and recommendation setups for your site. By hosting this tool within the Vinkius catalog, you get immediate access to advanced discovery tools alongside any other e-commerce service your team uses.
019d75c1-b49e-72ce-854c-7e583d4d7e66 How to set up Klevu (E-commerce AI Search) MCP
The bottom line is that this MCP turns complex product discovery into a simple conversation with your AI client.
Subscribe to this MCP and enter your Klevu Search URL and API Key.
Your AI agent uses the provided credentials to connect to your live e-commerce data.
You simply prompt your agent with a request, like 'Show me all blue shoes under size 10,' and it executes the search logic for you.
Who uses Klevu (E-commerce AI Search) MCP
This tool is critical for Digital Merchandisers and E-commerce Developers who spend too much time manually testing search paths or writing repetitive API calls. It’s also perfect for Data Analysts who need to monitor product performance trends without logging into a separate dashboard.
Audits the display logic on specific category pages and verifies that recommended products show up correctly based on current merchandising rules.
Tests search relevance, runs custom API queries, or validates product details for integration into a client application, all through conversational prompts.
Monitors global trending products and analyzes search performance to identify gaps in the catalog or untapped market interest.
Benefits of connecting Klevu (E-commerce AI Search) MCP
Bypass manual testing. Instead of repeatedly running separate queries for different filters, you can use the search_filtered tool to check complex combinations—like 'red shoes' and 'size 9'—all in one conversational prompt.
Optimize site performance by monitoring what sells best right now. Use the search_trending tool to identify global product velocity and quickly pinpoint seasonal opportunities, avoiding guesswork about inventory needs.
Control how products are displayed on your site. With search_category, you can audit whether a specific category page is correctly fetching all necessary related items according to your merchandising rules.
Go beyond basic searches. If the AI needs deep data—say, comparing multiple product attributes simultaneously—the search_raw tool lets you execute complex JSON payloads without needing specialized coding knowledge.
Improve user experience instantly. You can test how fast and accurate search results are by using search_autocomplete, ensuring that partial terms still guide users to the right products.
Klevu (E-commerce AI Search) MCP use cases
Checking for product gaps during a seasonal launch
A merchandiser needs to confirm if their new fall collection is showing up correctly across multiple related categories. They ask, 'Show me all items in the Winter Outerwear category that are blue.' The agent uses search_category and search_filtered together to provide a precise list of what's currently visible.
Debugging complex site search issues
A developer notices that 'waterproof jacket size 10' sometimes fails. Instead of writing multiple API calls, they ask the agent to run a targeted query using search_filtered and get a clean list, instantly confirming if the facet combination is supported.
Analyzing competitor product positioning
A data analyst wants to see what products are currently gaining traction globally. They ask the agent to run search_trending, getting an immediate overview of top sellers and high-demand items that they can use for inventory planning.
Building a recommendation engine prototype
A developer wants to test how product suggestions look. They ask the agent to execute search_recs on an existing search result, getting machine learning predictions without writing any backend code or managing external services.
Klevu (E-commerce AI Search) MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Assuming a simple keyword search is enough
Thinking that just searching for 'running shoes' will give them all the necessary data, when in fact they need to narrow it down by size and color.
Don't stop at basic keywords. Use search_filtered immediately after running a general search to apply specific facets like brand or size. Then use search_sorted if you want the results ordered by price.
Manually building every API request
Spending hours in Postman, writing separate JSON payloads for category checks, recommendation fetching, and keyword searches.
Use your AI agent. Simply ask the question: 'Check the recommended products on this page.' The agent handles the complex underlying logic, including calling search_recs or search_category, giving you a clean answer.
Forgetting about pagination limits
Running a search and only seeing 20 results, then assuming those are the only ones available.
After any search query, always follow up by asking for paginated results. The agent uses search_pagination to ensure you see everything available in the catalog.
When to use Klevu (E-commerce AI Search) MCP
Use this MCP if your core workflow involves discovery and auditing e-commerce logic. You need to know why a product appears where it does, or what happens when users search for complex combinations of attributes (e.g., 'leather boots' + 'size 12'). This is the right tool if you need conversational control over highly structured data sets.
Don't use this MCP if your only goal is to retrieve a single piece of static information, like fetching details for a known product ID—for that, search_product_id works perfectly. Also, don't use it if your task involves managing user accounts or processing payments; those require different types of APIs.
If you are struggling with complex filtering and need to check how products behave across categories, this MCP is the definitive solution. Otherwise, stick to a basic API connector.
Frequently asked questions about Klevu (E-commerce AI Search) MCP
How do I check if my product catalog supports complex filtering using Klevu AI Search MCP? +
You use the search_filtered tool. You just tell your agent what facets you want to combine, like 'color and size,' and it runs the query for you.
Can I find out what products are selling well right now using Klevu AI Search MCP? +
Yes. Use search_trending. This tool shows current top sellers, letting you monitor global product velocity and spot seasonal spikes instantly.
What if I need to run a query that the simple tools don't cover? Does Klevu AI Search MCP help? +
Absolutely. If your needs are highly specific, use search_raw. This tool lets you execute custom JSON search payloads against any deeply nested part of the Klevu API.
How do I get product suggestions for a user on my site? +
You run search_recs. The agent uses this to fetch predictions based on machine learning, giving you suggested items like 'frequently bought together'.
Does Klevu AI Search MCP handle product IDs for single lookups? +
Yes. If you know the ID number of a product, use search_product_id. This quickly retrieves all details for that single catalog item.