Most people don’t know is how Model Context Protocol (MCP) is about to change the game for Google Meet (big time!). In this post, we’ll cover what MCP is, what does the early access version of MCP for meetings looks like, what does the future looks like and how can you jump on the bandwagon right now. Let’s dig in!

Everyone knows Google Meet. It’s one of the top video conferencing platforms on the planet with over 300 million monthly users (more than double MS Teams!). 

MCP is a new protocol by Anthropic that’s designed to allow AI models to interact more intelligently with real-time meeting data. Imagine a world where your meetings aren’t just recorded but are transcribed and summarized, with the most important notes synced across your CRMs and project management tools instantly and automatically. All the tedious admin stuff you usually have to do? It’s done for you with MCP.

But… Google Meet MCP isn’t ready yet. If you wanted to set it up yourself, you could, but you’d need the tech know-how to create your own Model Context Protocol servers. If that sounds like Gibberish to you, then you might want to check out tl;dv, a tool that already does what MCP will do for Google Meet and other video conferencing platforms. More on that later, but first, what is Model Context Protocol?

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At its core, Model Context Protocol (MCP) is a new standard designed to make AI-powered tools smarter and more useful in real-time environments like virtual meetings. Think of it as a universal adaptor that aims to be the global standard that all future AI projects adopt. With MCP, AI models can extract real-world data and work with your tools (like Google Drive) autonomously.

If it still hasn’t sunk in yet, that means AI models will be able to pull real-time data from all your connected work tools without needing to ask you for permission or wait for a prompt. 

While this is MASSIVE news, it isn’t quite ready for the average Joe to simply plug and play. You need to know how to set up a server, host it, and work through MCP’s GitHub repositories. It’s certainly possible, but it’s a lot of work. Plus, there’s another solution that might just be more appealing. Before we dive into that, let’s look at what MCP could actually do if successfully integrated with Google Meet.

How MCP Improves Meetings

Imagine you’re in a Google Meet call, and instead of frantically taking notes or relying on someone else to summarize, an AI assistant automatically tracks key points, assigns action items, and generates a meeting summary—all in real time. That’s what MCP enables. It allows AI to not just record and transcribe meetings but also understand context: who’s speaking, what decisions are being made, and what follow-ups are required?

With MCP, meetings could become far more efficient and actionable. But the real power of MCP comes from its ability to integrate with other tools too. Imagine MCP as a digital pass for AI to enter your work tools on your behalf. It can take the meeting notes and automatically input them into your CRM system, generate and send follow-up emails, and even assign tasks across various collaborative tools.

Is Google Meet adopting MCP already?

So, is Google Meet adopting MCP? Not yet. While Google has been heavily investing in AI (see: Gemini, its response to ChatGPT), there’s no official confirmation that MCP is being integrated into Meet. However, Google has previously collaborated with Anthropic (the creators of MCP) on AI-related projects, so it’s not out of the question that some form of this technology could make its way into Meet in the future.

For now, Google Meet does offer some AI-powered features, like live captions, background noise cancellation, and meeting transcriptions. But true AI-driven meeting automation, the kind that MCP could enable, isn’t available yet. That means users looking for smarter, more automated meetings need to turn to third-party solutions that are already ahead of the curve.

If, however, you have the tech know-how and you’re in the mood for a little DIY, you can learn how to use Google’s Gemini 1.5 Pro model with Anthropic’s Model Context Protocol (MCP) via a community-made notebook hosted on GitHub. Developers are already exploring how to use Google products with MCP, so if they don’t officially release something, you can still get your hands on it.

Do you need an MCP for Google Meet?

Google Meet isn’t short on features, but when it comes to AI, it’s still operating at surface level. Right now, users get live captions, automatic transcription (if you’re on certain Google Workspace plans), noise cancellation, and some basic visual enhancements like lighting and background blur. Helpful? Sure. Smart? Not exactly.

Where it starts to fall short is in contextual intelligence. Tools like Anthropic’s MCP are designed to give AI a structured understanding of what’s happening in a meeting, but that level of semantic awareness and automation just isn’t baked into Google Meet yet. There’s no native action item tracking. No real-time summaries. No meeting memory. If you miss something, you’re digging through a transcript or watching a full recording. It’s not exactly efficient.

This is where MCP-like capabilities are needed. Imagine Google Meet automatically flagging action items as they come up, sending follow-ups, or letting you search across your meetings for “that moment when marketing approved the new campaign name.” That’s the future. But right now, the gap is clear: Google Meet’s AI is functional, but not yet intelligent.

If Google plans to integrate something like MCP (and they might, especially given their past collaborations with Anthropic), it’s not public yet. In the meantime, users looking for that next-gen AI meeting experience need to turn to tools that are already doing it.

MCP for Meetings: How can tl;dv help getting early access?

While the industry is abuzz with what might be coming with Google Meet MCP, tl;dv is already delivering many of those benefits today. It’s an AI meeting assistant that acts like the real-world MVP of what MCP is promising to be: smarter meetings, less manual work, and AI that actually understands context. 

You need only look at some of tl;dv’s features to understand the comparisons to MCP. Let’s take a look at three big ones, and then consider the future:

  1. Automatically filling out CRMs
  2. Multi-meeting intelligence and speaker analytics
  3. Scheduling recurring reports
  4. Ongoing innovation

1. Automatically Filling Out CRMs

tl;dv records, transcribes, and summarizes your virtual meetings, and it can sync these summaries and notes automatically with over 5,000 third-party tools, including deep integrations with CRMs. 

If we take sales as an example, this means that your reps don’t have to manually fill out customer information after each and every sales call. Instead, they can focus on the conversation and move swiftly onto the next one while the AI updates the CRM on their behalf. 

tl;dv provides custom meeting note templates so you can arrange your meeting notes in any way that you wish. These can be customized for different types of calls. For example, a sales call might be summarized in one format, while a candidate interview will likely utilize an entirely different format. You get the power to choose how the AI takes notes for you.

2. Multi-Meeting Intelligence and Speaker Analytics

tl;dv’s conversational intelligence is next level. Its AI is context-aware, with memory extending back through all your meetings. If you have a specific moment to find across all your meetings, you can talk to the tl;dv chatbot to quickly locate it. Even better, you can use the chatbot to analyze multiple calls at once, identifying patterns and trends that could be key to improving your business strategies.

This is a fantastic way to implement continuous sales training as reps can self-coach with AI guidance. There’s also a speaker analytics dashboard which covers averages like monologue length, filler words used, and talk-to-listen ratios. These can be compared to sales playbooks so reps can see where they need to improve. It’s also a place for sales managers to track whether reps are sticking to their sales scripts, with scorecards and even AI objection handling tips thrown into the mix.

3. Scheduling Recurring Reports

With tl;dv, you can schedule recurring reports to receive frequent updates straight to your inbox. Let’s say you want to receive weekly summaries from all your customer success team’s calls, especially highlighting those that talk about competitors. It’s as simple as selecting a few filters and then you’re away. Each and every week, tl;dv’s AI will send you reports about the specific topics you asked for across the specific meetings you want included. 

This is exactly how Google Meet with MCP will work. The only difference is tl;dv allows you to get started now, whereas Google’s potential MCP inclusion might take months, years, or it might not come at all. Sure, you can build one yourself if you have the time and resources, but you’ll also be missing out on calls from MS Teams or Zoom, which tl;dv also covers.

To put it simply, tl;dv is the early-access version of MCP you can actually use right now. It gives you a powerful, user-friendly interface, works across the meeting platforms you already use, and skips the usual AI-hype fluff. It just works—and it works today.

Ongoing Innovation: What Does the Future Have in Store for MCP and tl;dv?

While the giants are still testing the waters, tl;dv is out there building the boat, navigating the ocean, and sketching blueprints for the next vessel. tl;dv isn’t just reacting to where the market is going, it’s anticipating it. In fact, while MCP was only made open source a few months ago, tl;dv’s MCP-like features have been around for over a year. 

Whether it’s adding new cutting-edge features, improving transcription accuracy across languages, or designing smarter search and tagging workflows, tl;dv is moving fast. And while tools like Google Meet might eventually bring in MCP-style functionality, tl;dv will already be miles ahead, refining and expanding on what’s possible. Think of it less like “keeping up” and more like setting the standard.

So, for teams that want to lead rather than follow, don’t wait for Google Meet MCP. Take action and get started with tl;dv; it includes unlimited recordings, transcriptions, and summaries for free, and it takes about two minutes to create an account. There’s no reason not to give it a go.

Don’t Wait for the Future—Use It Now

The Model Context Protocol (MCP) is looking ready to make waves, especially if it’s adopted as the global standard. It brings real-time intelligence, automation, and contextual understanding into the AI world. While Google Meet could eventually adopt MCP or build something like it, the truth is: it’s not here yet.

What is here, right now, is tl;dv. If you’re looking for a tool that already delivers many of MCP’s promised benefits across Google Meet and beyond, then you’ve just found it. From searchable summaries to smart integrations, tl;dv gives teams a practical and intuitive way to supercharge their calls today.

If you’re tired of waiting for smarter meetings and want to get ahead while others are still planning their roadmap, tl;dv is your move. Try it now. Future you will thank you.

FAQs About Google Meet and Model Context Protocol (MCP)

MCP is an open protocol that allows AI models to understand and interact with real-time software environments, like meetings, cloud storage, and third-party tools. It provides contextual data so AI can deliver smarter insights, actions, and summaries.

As of now, Google Meet does not publicly support or integrate MCP. While Google is deeply invested in AI (especially through Gemini), there’s no official announcement connecting Meet to MCP just yet.

Google has collaborated with Anthropic (the creators of Claude and MCP) in the past and is an investor. However, there’s been no public confirmation from Google that they’re adopting MCP specifically within their tools like Meet or Docs.

MCP could power advanced AI features in Meet, such as real-time summarization, automatic action item tracking, smart follow-up generation, or even live insights during the call. It can also automate post-call workflows by automatically syncing meeting notes with CRMs and project management tools. Basically, it would make meetings more productive and less manual.

Tools like tl;dv already offer many MCP-like benefits, including searchable summaries, automated post-call workflows, and AI-generated meeting notes. tl;dv works across platforms (including Google Meet) and acts as an early-access version of what MCP could enable natively in the future.

No, but it doesn’t need to. tl;dv is independently built to solve the same core problems MCP aims to address, with its own infrastructure and UX built for immediate usability across meeting platforms.

Unless your team enjoys waiting on tech giants to roll out experimental features, don’t wait. tl;dv gives you most of the MCP magic today. You’ll future-proof your meetings and boost productivity now, not later.