The MCP Freemium Strategy
Plus: Updates from Hubspot, Miro, Monday, Pinecone, and Ahrefs.
Welcome back to Good Better Best.
Each week, we break down real pricing, packaging, and product moves from SaaS leaders and extract the ideas worth stealing.
This week, we’re digging into MCPs, and why companies are increasingly pushing MCP access into their free tiers. Since we just launched the PricingSaaS MCP, we wanted to dig into the different flavors of MCP, share how we’re thinking about it, and break down why we believe MCP access is a powerful way to drive free-to-paid conversion. First, the usual dose of pricing, packaging, and product news.
Let’s get to it.
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This Week in Pricing, Packaging, and Product
Hubspot offered a free trial for its Customer Agent [Link]
Ahrefs created prompt packages for Radar AI [Link]
Miro raised prices on the Business plan [Link]
Monday created an Enterprise AI bundle [Link]
Renderforest raised the price of the Business AI plan [Link]
Acuity Scheduling tweaked calendar limits [Link]
Pinecone launched a HIPAA compliance add-on [Link]
Moz added AI visibility features [Link]
Vendr restructured its plans [Link]
FullStory launched a Guides and Surveys add-on [Link]
Check out more updates on PricingSaaS →
The MCP Freemium Strategy
When we first started seeing MCPs in the wild, it wasn’t immediately clear how companies would monetize them. Some companies gated them behind premium plans, others didn’t. But as adoption has accelerated, and AI-native workflows have become more normalized, it’s becoming clearer where MCPs fit in.
MCPs can function as a feature, a usage accelerant, or power agentic workflows, but perhaps most importantly, they’re shaping up to be a powerful distribution channel.
If you’re new to MCPs, the easiest starting point is APIs, but there’s an important difference.
APIs allow developers to connect their product to other products, enabling their tools to work together. This makes both tools stickier by embedding each in the other’s workflow.
MCPs allow you to expose your product to the LLMs, allowing Claude and ChatGPT users to embed your tools directly into their workflow. But they also allow the LLMs to call on your tool when a user is looking for help on a use case that you help solve. This makes MCPs a powerful discovery engine.
This post on Lenny’s Newsletter about ChatGPT apps really drove the discoverability point home for me. ChatGPT apps are built on the MCP standard, and to build an MCP, you need to equip it with tools.
For example, with the PricingSaaS MCP you can browse our pricing changes, company histories, and search our research and thought leadership to do pricing research:
The money quote from the Lenny article is that these “tools” are the new battleground for AEO. In SEO, you fought to rank on a page. In AEO, you fight to be the tool a model calls. It’s not a perfect analogy, but the “tools” in your MCP showcase your relevance in a similar way to keywords in traditional SEO.
Here’s the author of the post, Colin Matthews:
Based on your tool’s name and description, ChatGPT can suggest your app to users to help solve their needs, like creating a slide deck or generating a financial model. Having accurate tool descriptions that uniquely identify your app will help ChatGPT users find and use your app in the correct contexts.
This distribution potential means it doesn’t really make sense to gate your MCP behind a paywall. At the very least, you should offer a free way to use your MCP to drive usage, then set guardrails to drive paid conversion.
This is exactly what we’re starting to see across some of the top players in SaaS, and we’ve observed a few different flavors.
Flavor 1: MCP as a feature (Otter.ai)
Otter offers their MCP for free, allowing users to pipe call transcripts directly into Claude/ChatGPT.
While Otter’s MCP doesn’t directly act as a monetization lever, it enables free users to get more out of the product, which indirectly drives usage, making it more likely users trip other usage limits.
Flavor 2: MCP as a usage accelerant (Zapier)
Zapier’s MCP allows you to connect to 8,000+ apps, which is particularly useful if any of those apps don’t have an MCP themselves.
Zapier’s free plan is limited to 100 tasks per month, and each MCP tool call counts as 2 tasks towards that quota. It’s easy to see how that could drive free-to-paid conversion for users that increasingly automate workflows out of Claude.
Flavor 3: MCP as part of an agentic workflow (Jam)
Jam.dev is like Loom for bug reporting, allowing developers to eliminate back and forth and debug faster.
Their MCP allows AI coding assistants to read complete, structured context from Jams to debug faster. Jam’s free plan is limited to 30 Jams, so similarly to Zapier, its easy to see a user blowing through that limit, especially if their team is using Claude code for debugging (a popular use case).
What we’re doing with PricingSaaS MCP
At PricingSaaS, we just launched our MCP this week, but we’ve been using it behind the scenes for the past month, and it has drastically changed how we work.
We’re using it to do rapid research projects for clients, curate weekly target account briefings for our partners, and to power our quarterly trend reports. Here’s a quick example, showing how you can use it to research AI credit models:
We’re still in beta, and don’t know exactly what pricing will look like, but we expect to keep MCP access free, and to follow a model similar to Zapier or Jam.
More broadly, there are two reasons I’d encourage any SaaS company to start experimenting with MCP:
An MCP helps power a credible AI story, especially if you become embedded in workflows for thousands of AI-native users.
As everyone scrambles to show up in LLMs, publishing an MCP (or ChatGPT app) will give you a leg up on the next big distribution channel.
We’re early — which means the opportunity is still wide open.
If you’re working on pricing and packaging research, give PricingSaaS MCP a shot and let us know what you think. If you have questions, shoot me a note at rob@pricingsaas.com.
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