GracenoteContent Data Business Unit NielsenAnnouncing the launch of a new product that will enable TV platforms to deliver user experiences that leverage large-scale language models (LLM) and Gracenote entertainment data.
The Gracenote Model Context Protocol (MCP) server connects LLM to the Gracenote knowledge base to validate, modify and enrich the responses to entertainment queries in real-time. This allows the platform to return accurate and relevant information to users based on content search input and discovery preferences.
Gracenote first rolls out the video MCP server, allowing CTV platforms and apps to benefit from LLM-driven inferences for search and discovery, while reducing restrictions.
When you dynamically connect to any LLM, the product validates and grounds the response of the Gracenote Entertainment data. This allows for a journey of discovery that utilizes conversation searches, personalized recommendations, and human-validated television, film and sports data.
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Gracenote Video MCP Server allows TV platforms to respond to queries, recommend programming and drive tune-in based on parameters such as:
- Show me an episode of Brooklyn Nine Nine.
- The Academy Awards will be held this week. List the 20 best Oscar-winning films from the past decade.
- Where can I watch the Dodgers game tonight?
In addition to the power of entertainment search and discovery, the product enriches LLM responses using Gracenote program images, availability information, and standardized content identifiers. This allows for harmony of data across a variety of sources and allows links to content such as reviews, trailers, ratings and more.
Tyler Bell, SVP, Products, Greycenote “Gracenote content data and IDs have long served as the source of truth in the global entertainment industry. With the launch of the Gracenote Video MCP server, we are leveraging both our data and technology to introduce a new wave of waves that will help our platform solve the big problems surrounding engineering and harmony.
Television platforms are exploring AI to improve search and discovery to deepen engagement and increase monetization. LLMS, a type of generator AI, allows you to create customised and harmonious content catalogs depicted in a wide range of training materials. It also allows for semantic searches and ranking of results based on user or editing criteria.
However, the output of LLM, even with ground, can be inaccurate, a phenomenon known as “hastisation.” LLM is limited to training information up to a certain point in time and does not have access to visual assets related to structured data such as television shows and movies.
Gracenote Video MCP Server is the first product in the company's AI suite developed to enable content search and discovery capabilities. As consumers become increasingly dependent on AI and LLMS, Gracenote's human-validated data serves as the source of truth for video, sports and music entertainment experiences.
