








Note: As of April 2025, we have sunsetted mcpt.com. After receiving immense interest in the registry, we had to make the hard decision that mcpt upkeep was not a bandwidth tradeoff we can make with our lean team. The following content has been left published for transparency.
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We're making it easier to build with MCP.
MCP servers connect AI apps with your product, and earlier this month we launched a way to generate them directly from your documentation.
Today, we're introducing mcpt—a managed registry where people can explore high quality MCP servers in one place.
Model Context Protocol (MCP) has exploded in popularity in just a few months since Anthropic's first introduced it a few months ago.
But at this critical moment when developers are most eager to learn and build, it's too hard for them to find quality servers. Some MCP registries exist, but they're either too small to be useful, or too crowded with user-generated servers that it's hard to find what you need.
mcpt is a managed registry that brings together high-quality third-party servers and official MCP servers generated directly from our customers' documentation.
What sets our curated directory apart is that Mintlify-generated MCP servers are always in sync with the latest updates—whenever documentation changes, the corresponding server updates automatically. This means anyone browsing mcpt always gets the most up-to-date and accurate view of your product's capabilities.
For those new to MCP, here's a quick refresher: the Model Context Protocol is a standard that provides a universal way for AI applications to connect with external data sources and tools.
MCP follows a client-server architecture:
As AI apps increasingly become the intermediary between your product and users, MCP servers play a crucial role in ensuring your product capabilities are accurately represented.
At Mintlify, we're rethinking how documentation can serve both human readers and LLMs.
Earlier this month, we launched our MCP Server Generator to automatically create servers from your existing documentation or OpenAPI spec, without any custom code needed.
These docs-based servers enable AI applications to:
Beyond MCP, we've released many improvements for AI documentation consumption:
We're investing in MCP to drive AI adoption across the developer and broader community, as we see it as a fundamental shift in how products integrate with AI tools.
But ahead of widespread usage, MCP faces two key challenges: distribution and usability. We're tackling the distribution challenge with mcpt, and we have more coming soon for the latter.
It's never been a better time to build and we're excited for what's next.
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