Ask in plain language: "Who leads my category?", "Why did this product drop?", "What should I fix first?" Answers come from your own Novi data.
Connect Claude or ChatGPT to Novi and work with category strategies, leaderboards, share-of-voice history, citation sources, page audits, AI-ready content and implementation guidance inside the assistant.
Draft a client readout, brief a content team, or check a page against the category strategy without leaving the tool where the work happens.
Go beyond dashboards with direct access to Novi's Category Intelligence. Ask specific questions about your products, uncover the attributes influencing AI recommendations, and get actionable guidance to improve performance.
Example:“Which three attributes are costing our top SKU rank in ChatGPT, and what should the FAQ say?”
Connect Novi MCP through your AI assistant’s connector settings and sign in with your Novi account.
Your assistant securely accesses the same Novi data and permissions available to your account, with read-only access.
Ask questions in plain language about your categories, product performance, competitors, or optimization opportunities.
Get data-backed answers, insights, and actionable recommendations directly from your stored Novi intelligence.
Novi complements your existing AI visibility tools with category-level intelligence that reveals what drives product recommendations, where your products fall short, and which optimizations matter most.
Talk to salesNovi MCP connects Novi’s AI shopping intelligence with AI assistants through the Model Context Protocol (MCP). It allows teams to access category intelligence, product rankings, citation sources, and optimization insights from supported AI tools.
The Model Context Protocol is an open standard that allows AI assistants to connect with external tools and data sources. It enables assistants to retrieve relevant information from connected systems and use that context to answer questions and support workflows.
Ask Novi lets users ask questions about their product and category data directly within the Novi platform. Novi MCP extends access to that intelligence through external AI assistants, allowing teams to work with Novi insights within their existing workflows.
Teams can use Novi MCP to explore category strategies, review product rankings, investigate citation sources, and access product optimization recommendations. For example, a team could ask which attributes matter most in a category or what changes may help improve a product’s AI recommendation performance.
