MCP Registry: The Missing Link in AI Tool Interoperability

If you’ve been following my posts, you already know how much I’ve been exploring the Model Context Protocol (MCP). Over the past months, I wrote about it and built servers and clients around it, from dynamic server generation tools to MCP-powered assistants that connect real APIs. That hands-on experience made it clear to me how powerful this standard can be and how much potential it has to simplify AI integrations.

But there was always one missing piece.

Every time I created a new MCP server, I had to explain where people could find it and how to connect. There wasn’t a single place that listed all the community-built servers . There was no central hub for discovery or trust. You either shared links manually or stumbled upon projects through GitHub or Discord.

That is now changing.

A Single Source of Truth for MCP Servers

Anthropic has launched the MCP Registry (still in a preview phase): an open catalog and API that makes publicly available MCP servers easy to find, integrate, and trust.

You can check it out here: registry.modelcontextprotocol.io.

It acts as a central hub where developers can publish and discover MCP servers. And because it’s open source, it’s not just a static directory. In fact, it’s the foundation for an entire ecosystem of sub-registries, both public and private.

For me, this fills a huge gap.

Why This Matters

The MCP Registry has the potential of changi how AI systems connect with the world.

If MCP is the protocol that lets AI agents “talk” to tools, the registry is the map that shows them where those tools are and how to use them.

Here’s why that matters:

• It standardizes how servers are described and distributed.
• It simplifies discovery for both developers and clients.
• It builds trust through community moderation and transparent entries.
• It enables growth, allowing public or private registries to build on the same backbone.

When I think about the future of MCP-powered applications , AI assistants that can book flights, manage tasks, or control business workflows, having a common registry means we can move faster and collaborate better across projects.

Public and Private Sub-Registries

One of the most exciting parts of this release is how flexible it is.

Public sub-registries can act as AI marketplaces. Imagine an IDE like VS Code automatically surfacing all compatible MCP servers or a Copilot-like assistant suggesting new tools you can connect on the fly.

Private sub-registries can power enterprise environments. At Cisco, for example, we could build an internal MCP registry that connects our AI agents to case management or data systems securely, all while using the same open API schema as the public registry.

Both approaches rely on the MCP Registry as the upstream source of truth.

Getting Started (Preview Phase)

The MCP Registry is currently in preview, which means it’s available for testing and feedback before its general release. There may still be breaking changes or missing features, but it’s the perfect time to get involved.

For server maintainers: You can now add your MCP server to the registry by following the official guide: Adding Servers to the MCP Registry

For client developers: You can already access server data through the public API and start building MCP-compatible clients: Accessing MCP Registry Data

Because this is a preview release, the data isn’t guaranteed to be persistent or final , but it’s an excellent chance to explore how the ecosystem will look and help shape it with your feedback.

The Bigger Picture

With MCP Registry, every AI assistant, IDE plugin, or LLM client will be able to pull from the same unified catalog of available tools. That means faster development, better collaboration, and a much richer ecosystem of AI capabilities.

The MCP Registry isn’t just about listing servers. It’s about interoperability.

Having worked with MCP from its early stages, this feels like a real milestone, a sign that the ecosystem is moving from experimental to structured, from promising to practical.

Final Thoughts

If you maintain an MCP server, I believe it is time for you start exploring how to add it to the registry and make it discoverable.

If you’re building an AI client or assistant, start exploring the registry API. It’s the easiest way to stay connected to the growing network of MCP servers.

For me, this launch feels like the GitHub moment for MCP: a foundation that connects, organizes, and amplifies everything the community has been building.