NLWeb: Tapping MCP for natural language web search

“This is the single biggest … most positive change we’ve had in the last five years and perhaps one of the biggest since the beginning.” Pandu Nayak, Google fellow and VP of search, about adding transformer models in production at Google. Interestingly, this progress didn’t apply to just one type of task like question answering, but across the board to almost every single NLP task. These models learned sufficient general knowledge of language to perform well on a huge range of NLP benchmarks.

Unstructured information management

As machine learning technology continues to shock the world, popular artificial intelligence tools such as natural language processing may generate unforeseen issues for humanity. His work has appeared in leading publications including InfoWorld, CIO, CSO Online, and IBM developerWorks. Matthew also has had the privilege of interviewing many tech luminaries including Brendan Eich, Grady Booch, Guillermo Rauch, and Martin Hellman. The ability of computers to recognize words introduces a variety of applications and tools. Personal assistants like Siri, Alexa and Microsoft Cortana are prominent examples of conversational AI. They allow humans to make a call from a mobile phone while driving or switch lights on or off in a smart home.

How the revolution of natural language processing is changing the way companies understand text

Retailers, health care providers and others increasingly rely on chatbots to interact with customers, answer basic questions and route customers to other online resources. These systems can also connect a customer to a live agent, when necessary. Voice systems allow customers to verbally say what they need rather than push buttons on the phone. Currently, it is usually not powerful enough to produce fully grammatical and idiomatic translations, but it can give you the gist of a web page or email in a language you don’t speak.

• The company is more than 11 years old and it is integrated with most online environments where text might be edited.
• One of the primary use cases for artificial intelligence (AI) is to help organizations process text data.
• Today, the company announced the release of a multilingual text-understanding LLM that can understand and work with more than 100 different languages.
• Natural language processing is a field in machine learning where a computer processes human language through vast amounts of data to understand, translate, extract, and organize information.

We can access the array of tokens, the words “human events,” and the following comma, and each occupies an element. Let’s build up a basic application that we can use to see how OpenNLP works. We can start the layout with a Maven archetype, as shown in Listing 1. One real-world application of NLP that strikes Leichenauer is as a smart assistant for writing code.

MCP C# SDK updated to support latest Model Context Protocol spec

This capability is also valuable for understanding product reviews, the effectiveness of advertising campaigns, how people are reacting to news and other events, and various other purposes. Sentiment analysis finds things that might otherwise evade human detection. Google offers an elaborate suite of APIs for decoding websites, spoken words and printed documents. Some tools are built to translate spoken or printed words into digital form, and others focus on finding some understanding of the digitized text. One cloud APIs, for instance, will perform optical character recognition while another will convert speech to text.

This enables developers to operate more efficiently and also allows for low-code and no-code solutions that are more powerful than before. Results are displayed in either a drop-down menu or in a classic search engine UI. Both options allow you to refine results by giving more context through a chat. NLWeb can be used to render results based on their Schema.org item type. A sample recipe display script is included as part of the NLWeb repository. At the same time, as queries are grounded in your website data, and results returned as lists, you’re able to first check for relevance and errors and reject incorrect responses.

Natural language processing is a lucrative commodity yet has one of the largest environmental impacts out of all the other fields in the artificial intelligence realm. The process used to train, experiment, and fine-tune a natural language process model has been estimated to create on average more CO2 emissions than two Americans annually. Announced at Build 2025, NLWeb is an open project that’s intended to run alongside existing web properties, allowing the use of any model to add voice and text inputs that go beyond basic click-based navigation. Technologies like Model Context Protocol (MCP) are reshaping both how we build AI-powered applications and what we can do with them. By providing a standard way of describing and accessing information stored in our applications, MCP makes it easier to add AI features to existing code and services.

While the need for translators hasn’t disappeared, it’s now easy to convert documents from one language to another. This has simplified interactions and business processes for global companies while simplifying global trade. Natural language processing uses artificial intelligence to replicate human speech and text on computing devices.

That bet has resulted in many different experiments and projects, across the company and its various divisions. One of the more interesting approaches is intended to standardize building natural language interfaces for websites and web applications. This builds on one of the strengths of modern generative AI models, their ability to transcribe speech and assign intent to the results, providing a new level of accessibility as well as supporting machine-to-machine interactions. For example, the technology can digest huge volumes of text data and research databases and create summaries or abstracts that relate to the most pertinent and salient content. Similarly, content analysis can be used for cybersecurity, including spam detection. These systems can reduce or eliminate the need for manual human involvement.

Describing NLP as the analysis and generation of natural language with computers, he says, it is the use of Large Language Models (LLMs) and chatbots that are driving a lot of the excitement around the subject. Let’s look at some of the main ways in which companies are adopting NLP technology and using it to improve business processes. More specialized tools can be added, with a set of tools for working with recipes part of the first release. These can help substitute ingredients or find the right accompaniments. For your own use cases and content, you can define and add your own tools for your own specific use case, working with the project code and extending and changing as necessary.