GitHub has thrown its hat into the AI interoperability space with the launch of its very own MCP Registry, serving as a curated directory for discovering and evaluating MCP servers — the connective tissue that lets AI agents and external tools interoperate.
MCP (Model Context Protocol), for the uninitiated, is an open-source specification introduced by Anthropic last year to give AI systems a common language for fetching data, invoking tools, and sharing state — essential plumbing that connects AI agents to the outside world. So if, for example, a developer wants an AI agent to grab customer tickets from Zendesk, update a Trello board, and summarize it all in Slack, MCP defines the pipes that help the hand-offs flow more freely.
With the GitHub MCP Registry, developers can access a centralized place to discover, assess, and connect to the growing number of MCP servers appearing across the ecosystem.
A growing field of MCP registries
At launch, the GitHub MCP Registry features a catalog of more than 40 servers, spanning integrations from productivity tools like Notion and Figma to infrastructure players such as HashiCorp and Dynatrace.
The registry’s arrival comes at a time when both AI agents and MCP servers are exploding in numbers, as developers scramble to wire intelligent assistants into every conceivable workflow. Yet while open source projects and startups alike are spinning up their own MCP servers to expose functionality, discovery and trust remain fragmented.
It also lands against a backdrop of parallel efforts to bring order to the growing MCP ecosystem. This includes what could be considered an “official” registry launched in September by the Model Context Protocol project itself. Designed as a kind of registry of registries, that community-governed index offers open APIs and schemas that let anyone build sub-registries or automated discovery tools on top, serving as the protocol’s backbone rather than a curated marketplace.
Elsewhere, hosted platforms like MCP.run take a more hands-on approach. Instead of simply listing servers, MCP.run actually hosts and manages them, giving developers an easy way to connect to shared MCP servers without running their own infrastructure. It positions itself as a “control plane” for MCP, offering profiles, configuration management, and team sharing — useful for teams who want to experiment quickly but don’t want to deploy servers themselves. GitHub’s twist on the MCP Registry, meanwhile, is all about trust: it’s entirely curated, with every listing anchored to a public repository. This allows the same social signals that power open source projects — stars, forks, and commits — to help developers judge which MCP servers to wire in.
“We’re starting simple and building in the open,” Toby Padilla, a GitHub product manager who leads the company’s MCP initiatives, wrote in a blog post. “The MCP Registry launches with a curated directory of MCP servers from leading partners and the open source community. Each server is backed by its GitHub repository, so you can learn what it does, how to get started, and make informed choices quickly.”
Notably, Padilla is also listed as one of the early maintainers of the “official” MCP Registry, alongside contributors from companies such as Anthropic and Block. It’s a clear signal that GitHub’s work isn’t a competing effort, but part of a broader, coordinated push to make MCP’s discovery layer a shared standard.
Rather than rivals, the two registries appear to function as complementary halves of the same ecosystem — one defining the open plumbing, the other providing the interface and trust layer that connects it to developers.
The community reacts: curation for the win
The community was quick to observe the emergence of two MCP registries in quick succession, with one Hacker News commenter noting in response to GitHub’s launch that “there is also a first-party registry in development, hopefully becoming the next Artifact Hub for MCP servers.” The comment — referencing the Cloud Native Computing Foundation’s community-run catalog for cloud-native components — hints at what some developers hope MCP’s discovery layer could eventually become.
Over on Reddit, meanwhile, one user reflected a sense of fatigue at yet another registry (“another week, another MCP registry”), but conceded that a little curation might not be such a bad thing given the flood of experimental MCP servers now popping up.
“A more curated list of MCP servers is helpful, as there are just so many servers, many of which are created by hobbyists and are, thus, untrusted / unvetted,” they wrote.
In response, another Reddit user humorously questioned whether there will be a “registry of curated MCP registries next.”
Whether the ecosystem consolidates or continues to splinter, GitHub’s entry gives the MCP movement a credibility boost, and a clearer path toward standardizing how AI agents find and trust the tools they rely on.
