I’m thrilled to share that Profound Agents now seamlessly integrate with Webflow. This new capability transforms your CMS into an active automation endpoint, streamlining processes and boosting efficiency.
This integration is designed to elevate how you manage content, providing newfound ease and automation right at your fingertips. It marks a significant step forward in optimizing digital workflows, empowering me to focus more on creativity and less on manual tasks.
I’m excited to share with you the newest feature in Profound: Custom Dashboards! This innovative tool lets me create personalized, fully configurable, and shareable views of my data, all tailored to fit my unique needs.
Having the ability to build these dashboards transforms how I interact with my data. With just a few clicks, I can design views that help me better understand and analyze crucial insights. Whether for personal use or sharing with a team, these dashboards are an invaluable addition to my data toolkit.
The convenience and flexibility of Custom Dashboards have genuinely enhanced my workflow. Now, I can focus on making data-driven decisions with confidence, knowing that my data is presented precisely the way I need it. Join me in exploring this exciting feature, and let’s make the most of our data together.
I’m excited to share that I can now effortlessly integrate Google Search Console data directly into any of my Profound Agents. This powerful combination, uniting Search Console insights with Profound’s answer engine data, is transforming how I handle reporting, content creation, monitoring, and optimization.
Staying on the Profound platform makes the entire process seamless, allowing me to focus on what truly matters—building and optimizing my digital strategies without the hassle of platform switching.
Recently, while exploring the latest developments in web technology, I stumbled upon something groundbreaking: WebMCP, introduced in Chrome 146. Being a tech enthusiast, I was intrigued to learn how this emerging protocol could reshape the way AI agents interact with websites.
Chrome 146 has rolled out an exciting early preview of WebMCP, hidden behind a flag. This protocol, known as Web Model Context Protocol (WebMCP), is designed as a web standard to lay out website tools in a structured manner, guiding AI agents in executing tasks seamlessly.
So, what does this mean for us? Historically, the internet has been developed with humans in mind. Buttons, forms, and dropdowns are all elements we understand. But there’s an emerging user—AI agents. Soon, they will be completing registrations, purchasing tickets, and achieving other goals autonomously on websites.
Currently, AI agents face a daunting task. They navigate websites by crawling and attempting to decipher their functionalities. Imagine an AI agent trying to book a flight. It has to identify input fields, guess data formats, and pray nothing goes awry. It’s far from ideal.
The introduction of WebMCP is set to change this. By exposing the structure behind web tools, AI agents will be equipped to understand and execute tasks with ease.
Let’s dive a bit deeper to understand WebMCP. Picture yourself needing to book a flight.
Without WebMCP: An AI agent scrambles to find a relevant button like “Book a Flight” or “Search Flights.” It then interprets the on-screen information, hoping it inputs correctly.
With WebMCP: Forget searching for buttons. Instead, the agent calls a function, like bookFlight(), using well-defined parameters (such as date, origin/destination, and passengers), receiving a structured result in return. Much like developers interacting via APIs, AI agents will seamlessly call functions.
WebMCP empowers websites with JavaScript APIs and HTML form annotations, guiding AI agents on interacting with web tools in three steps:
Discovery: What tools does the page support? Examples include Checkout, BookFlight, or searchProducts.
JSON Schemas: They precisely define expected inputs and the kind of output that will be returned.
State: Tool availability alters based on the page’s state, allowing agents to only see actions relevant to the current context.
My website, for instance, could offer a list of actions each detailing its functionality, accepted inputs, returned outputs, and required permissions.
But why does this matter? AI agents are infiltrating our daily workflows rapidly. Soon, AI will handle our flight bookings, fill out forms, and publish content. But, as of now, AI agents struggle to interact seamlessly with websites due to two current approaches:
Automation (fragile): An AI acts by clicking buttons and inputting data like we do, but since websites frequently update, this can lead to failures.
APIs (limited): While APIs offer a structured approach for interaction, they’re not universally available or comprehensive.
WebMCP offers a middle ground, allowing websites to make tools accessible without the drawbacks of UI automation or needing separate APIs.
Like the early 2000s SEO race, WebMCP symbolizes a shift towards optimization for AI agents. Those who adopt this early could enjoy significant advantages as AI-centric search and commerce grow.
This opportunity is not merely about SEO anymore. It’s about realizing broader growth potential through WebMCP, which signifies not just being discoverable, but actionable by AI agents who’ll soon connect with future customers.
Practical applications of WebMCP in B2B and B2C scenarios are vast, from simplifying quote requests to expediting inventory checks, offering a seamless experience for business and everyday consumers alike.
To start experimenting with WebMCP, Chrome 146 lets you access it behind a feature flag. It’s still in its nascent stage but provides a valuable chance for developers and innovative teams to play around with the conceptual framework.
While getting acquainted with WebMCP, you’ll need Chrome version 146.0.7672.0 or later and a basic understanding of Chrome flags. Follow these steps to set up:
Navigate to chrome://flags/#enable-webmcp-testing in Chrome.
Set the “WebMCP for testing” flag to “Enabled”.
Relaunch Chrome.
Start experimenting with WebMCP today and perhaps even install the Model Context Tool Inspector Extension to witness WebMCP in action. It’s an exciting era we’re stepping into, enabling websites to be as understandable to AI as they are to us.
The landscape of AI is rapidly shifting in 2026. I’ve noticed that AI models are losing their once shared data access, resulting in fragmented and less cohesive answers.
This change is primarily due to the surge in platform-controlled data, which is significantly altering how visibility and search functions within AI systems. It’s intriguing to see how these developments are reshaping the way we interact with and trust AI-driven responses.
As I delve into the world of AI searches for wearable technology, I’ve noticed a fascinating trend. It turns out that trusted third-party sites are more frequently favored over brand websites. This piqued my curiosity, and I wanted to dig deeper into these patterns and uncover how one can achieve AI visibility.
One of the key aspects that stood out is the consistency in how certain domains are cited across AI searches. These sites have established a level of trust and authority that AI algorithms consistently recognize. As I’m navigating through this data, I’m exploring the most frequently cited domains in this realm and the trust patterns they demonstrate.
Gaining AI visibility isn’t just about being present; it’s about earning trust and authority. By understanding these patterns, I feel more equipped to help others and myself in enhancing the visibility of our wearable tech offerings.
I’ve discovered how essential it is to integrate trusted search intelligence across our enterprise. With the Conductor Data API, we’re extending these capabilities in ways I hadn’t imagined.
Seeing our data work harmoniously across platforms feels transformative, allowing us to leverage AI infrastructure like never before. This powerful insight has reshaped how we view our enterprise integration strategies.
As someone deeply involved in marketing, I know how crucial it is to have access to accurate and comprehensive company information. That’s why when our marketing team uses Profound to upload Knowledge Bases, it gives us a single source of truth for company-specific data.
This capability empowers us, as agents, to provide the right context about your brand every time we execute a marketing action on your behalf. This streamlined approach ensures consistency and accuracy in representing your brand.
I’ve always been fascinated by the intersection of AI and healthcare, and every month I eagerly anticipate the newest updates. The Goodie team curates these insights, letting us peek into the dynamic shifts within the AI and medical sectors.
Imagine the transformative potential of AI in healthcare. From diagnostics to patient care, companies like OpenAI, Google, and Anthropic are leading the charge, each with unique contributions and innovations.
Imagine a world where workflows evolve beyond mere manual processes, actively collaborating with us as marketers. That’s the future Agents bring to life, seamlessly integrating with our marketing teams as valued members.
In the past month, the dedicated team behind Agents has released a series of updates, ushering in new capabilities that promise to change the way we approach marketing tasks.
