Your Subsequent Consumer is an AI Agent
“From the primary webpage we constructed for people to the primary Mannequin Context Protocol we constructed for an AI agent. We’re getting into a brand new period the place your web site’s most vital customer isn’t an individual, it’s an agent.”— @cyberandy
By 2027, AI-driven suggestions are projected to information over $1 trillion in annual international e-commerce purchases (Statista, McKinsey), representing 10–15% of the anticipated $9–10 trillion e-commerce market (GlobalData).
This transformation is already underway — over 35% of Amazon’s gross sales are attributed to AI-powered product suggestions (McKinsey, 2023), and voice commerce is anticipated to achieve $150–420 billion globally by 2030 (Statista, Juniper Analysis).
MCP is inevitable — identical to HTML was within the ’90s. https://t.co/SLUrD4Xhgf
— Andrea Volpini (@cyberandy) March 31, 2025
At WordLift Labs, we’ve lengthy been serving to shoppers put together their web sites for AI-driven discovery via structured knowledge and semantic applied sciences. In the present day, we’re taking this mission additional by embracing the Mannequin Context Protocol (MCP) — a brand new commonplace that permits AI brokers to work together together with your content material, instruments, and knowledge in actual time.
From Structured Knowledge to llms.txt to MCP
We began with schema.org markup. Then we helped promote llms.txt — a brand new commonplace, very similar to robots.txt, that tells generative AI which content material is optimized and accessible for indexing.
However the subsequent leap isn’t just making content material seen, it’s making it usable by AI.
That’s the position of MCP.
With MCP, your product catalog, inventory ranges, return coverage, and different enterprise knowledge will be uncovered via a standardized, structured interface, making them accessible to AI brokers through a single integration. One protocol, one data graph — and numerous new prospects for clever interplay.
A Glimpse into the Future: SARA, Our Purchasing AI Prototype
To showcase what’s doable when web sites are actually AI-ready, we constructed SARA — a voice-powered Purchasing AI Analysis Assistant. SARA is powered by structured knowledge and our semantic data graph, and was prototyped utilizing AutoGen, Microsoft’s framework for multi-agent collaboration.
In our early experiments, brokers labored collectively to assist customers choose the suitable product, examine choices, and refine preferences via dialog.
SARA affords a glimpse of what’s subsequent: a world the place AI brokers change conventional search interfaces, and protocols like MCP function the infrastructure layer connecting AI techniques to dwell knowledge and instruments.
WordLift’s AI Voice Purchasing Agent – SARA
AI Brokers Are Reshaping eCommerce
One thing large is going on in eCommerce. You may really feel it in each chatbot interplay, AI-generated advice, and voice command we whisper into our telephones.
Whether or not it’s inserting an order via Alexa, getting customized product strategies from a chatbot, or hands-free purchasing whereas cooking dinner — AI brokers are altering how we uncover, examine, and buy merchandise.
We’re additionally seeing the rise of generative AI in transactional queries, with Google’s AI Overviews reshaping how consumers interact on the prime of the funnel. Think about instruments like Manus AI or OpenAI Operator evolving to sift via product catalogs in actual time, examine specs, and make knowledgeable buying selections on our behalf. The way forward for on-line purchasing won’t simply be assisted — it will likely be delegated.
This transformation isn’t just about comfort. It marks a brand new period of accessibility, personalization, and effectivity. From Estée Lauder’s voice-enabled make-up assistant for visually impaired customers to Walmart’s Google Assistant integration, we’re witnessing tangible examples of AI-driven innovation in motion.
At WordLift, we imagine AI brokers will redefine digital advertising and marketing and search engine marketing. However for these brokers to be actually efficient, they want entry to the suitable context — and that’s the place the Mannequin Context Protocol (MCP) comes into play.
Contact us for Enterprise Prepared MCP
We’re working with e-commerce manufacturers and retailers to create their MCP stacks, enabling AI brokers to devour their knowledge and context in standardized methods.
Introducing the Mannequin Context Protocol (MCP): The HTTP of AI Techniques
The Mannequin Context Protocol (MCP) is an open commonplace that permits AI brokers to attach with real-time, structured context — from product catalogs and availability knowledge to advertising and marketing instruments and assist techniques.
Consider MCP not simply as HTML for AI brokers — however because the HTTP layer for clever techniques. It gives a shared protocol for context supply: a manner for AI fashions to securely and reliably entry the structured knowledge and actions they should carry out significant work.In the identical manner that HTTP enabled the World Vast Internet, MCP allows the Agent Internet.
Why MCP Issues for SEOs and eCommerce Groups
Search is evolving. More and more, it’s not a consumer typing into Google — it’s an agent appearing on their behalf, whether or not via voice, chat, or embedded AI in apps.
Conventional search engine marketing has centered on optimizing content material for people and search engine crawlers. However AI brokers function in a different way — they want structured, machine-actionable context to retrieve, cause, and reply. That’s precisely what MCP allows.
With MCP, brokers can:
Retrieve real-time product availability
Entry pricing and stock techniques
Provide dynamic, customized product suggestions
Work together with assist techniques, return insurance policies, or CRMs
For SEOs, this opens up a brand new dimension of optimization: designing your digital infrastructure not only for visibility, however for agent usability.
MCP in Apply: search engine marketing Instruments You Can Use In the present day
To assist SEOs and technical entrepreneurs discover the Mannequin Context Protocol (MCP) and start constructing agent-first workflows, right here’s a curated record of MCP-compatible instruments and servers. These instruments allow AI brokers to carry out key search engine marketing duties — together with audits, analytics, structured knowledge validation, and content material technology — via a standardized and safe protocol. Whereas I haven’t extensively examined every device in manufacturing, they signify a few of the most promising and accessible beginning factors for experimenting with MCP in real-world situations.
🔧 search engine marketing Inspector & Schema Validator
Detects search engine marketing points and validates JSON-LD structured knowledge immediately in your codebase.
Works inside Cursor IDE with out browser extensions.
Checks: Titles, meta descriptions, headings, canonical tags, schema varieties.
🔍 search engine marketing Audit Instrument on Apify
Full-site search engine marketing audits: damaged hyperlinks, gradual pages, lacking photos.
Integrates with Apify API or through MCP-compatible brokers.
Best for automating technical checks and website well being diagnostics.
📈 DataForSEO MCP Server (by Skobyn)
Entry to look quantity knowledge, SERP snapshots, backlinks, and domain-level insights.
Allows AI-driven key phrase analysis, aggressive evaluation, and rank monitoring.
Full MCP interface over DataForSEO APIs.
📊 Google Search Console MCP Server
Bridges GSC search analytics into your agent workflow through MCP.
Options:
Dimension filtering (queries, pages, gadgets, international locations)
Customized date ranges
Use instances: efficiency evaluation, agent-generated studies, question intent monitoring.
🧠 Claudeus WordPress MCP
AI-powered WordPress administration system with search engine marketing tooling.
Options: AI content material creation, schema validation, inner linking.
Standing: Below growth
🧪 WordLift’s eCommerce MCP Server (Non-public Preview)
What it does: Supplies AI brokers with safe, structured entry to a product data graph through neural search and exposes all of the instruments and workflows of Agent WordLift via the Mannequin Context Protocol.
Options:
Entry to product knowledge through semantic and vector search
Structured prompts for content material technology, optimization, and enrichment
Integration with workflows for inner linking, product suggestions, and content material evaluation
Use case: Allows store homeowners and builders to create AI-powered purchasing assistants (like SARA) and construct absolutely agent-ready eCommerce experiences, powered by real-time data and actionable instruments.
Entry: Request entry or demo right here.
🌐 mcp.so – The Mannequin Context Protocol Listing
A community-driven platform that catalogs third-party MCP servers.
Nice for locating new instruments, studying about use instances, and sharing your individual.
Bookmark this for those who’re critical about constructing agent-first workflows.
From Idea to Apply: Constructing AI-Powered Wine Assistants with MCP
The Italian wine advice system leverages a specialised wine data graph and ontology to create a semantically wealthy search expertise that may be accessed by AI brokers.
At its core, the system makes use of WordLift’s vector search API to question a structured data graph the place wines are organized in response to a complete wine ontology.
This ontology contains crucial wine attributes like wine:sort.worth (crimson, white, rosé), wine:grapeVariety.worth (Vermentino, Sangiovese, and many others.), wine:area.worth (Toscana, Piemonte), wine:aroma.worth, and different specialised properties like alcohol content material, manufacturing methodology, and high quality classifications.
When a consumer or AI agent submits a question via LangGraph, the system interprets pure language requests into structured filters that align with this ontology. For instance, when trying to find “vermentino sotto i 20 euro,” the system doesn’t simply carry out key phrase matching however understands that “vermentino” maps to the wine:grapeVariety.worth property and “sotto i 20 euro” interprets to a value constraint utilizing the ex-private:priceEUR property with an acceptable operator (LT for “lower than”).
The Mannequin Context Protocol (MCP) server acts because the bridge between AI brokers and this information graph, exposing a standardized interface that any AI system can use—whether or not it’s Gemini, Claude, or a customized agent.
This implies the wine experience embedded within the data graph turns into instantly accessible with out every AI needing to be particularly educated on wine data. The MCP server handles the complicated question development, authentication, and consequence formatting, permitting AI brokers to deal with understanding consumer intent and presenting outcomes.
What makes this strategy notably highly effective is its capacity to deal with complicated, multifaceted queries that mix attributes in methods conventional search techniques wrestle with. As an example, an agent might request wines that match particular meals pairings, come from sure areas, and fall inside value ranges—all whereas contemplating availability. The system may even assist extra complicated logical operations via OR filters, enabling queries like “discover me a white or rosé wine that pairs with seafood.”
By structuring wine knowledge in response to this specialised ontology and exposing it via MCP, we’re enabling AI brokers to turn into refined wine consultants that may automate beforehand human-exclusive experience in wine choice and meals pairing—making your complete catalog semantically accessible for next-generation AI purchasing assistants.
Wanting Forward
The rise of AI brokers isn’t a pattern — it’s the inspiration of the following period of on-line commerce. With MCP, we now have the infrastructure to make these brokers actually clever, linked, and helpful.
At WordLift, we’re dedicated to creating these improvements accessible. Whether or not you’re optimizing a retailer, constructing AI workflows, or enhancing product discovery, be a part of us in shaping the way forward for eCommerce.
Let’s empower our AI brokers to do extra — with higher context and smarter instruments.We automate the creation of MCP servers immediately out of your product data graph — making it straightforward to attach your product catalog with AI brokers and develop your online business.
👉 Fill out this type to attach your product catalog with AI Brokers through MCP
The age of semantic commerce has arrived.
Sources to study extra
To deepen your understanding of the Mannequin Context Protocol (MCP), listed below are just a few assets:
