Life cycle and performance
As a tagalong to security guardrails, an MCP registry is an opportune location to introduce supply chain security features and monitoring.
“This includes vetting servers before they’re discoverable, implementing security scans and vulnerability checks, and controlling what can be published or discovered,” says Alex Salazar, co-founder and CEO at Arcade.dev, provider of an AI tool calling platform. Salazar says that registries should track performance metrics and errors, as well.
In addition to dynamic tool discovery and tooling governance, Marco Palladino, CTO and co-founder of Kong, provider of a cloud-native API platform, sees observability across the AI data path as necessary for an enterprise-grade MCP registry.
“Enterprises need centralized visibility into tool usage, health, and failures to support monitoring, optimization, cost management, and compliance,” says Palladino. “Without this, organizations face fragmented integrations and increased operational risk.”
Beyond the above areas, experts foresee that other attributes will be necessary for MCP registries in an enterprise context:
- Fingerprinting of the tools within a particular server
- A bridge between private and public registries
- Ranking or scoring based on previous performance, token cost, and other attributes
- Namespace verification to prevent naming conflicts
- Validation layers to catch errors
- Health monitoring to track server availability and performance
Choosing a public or private MCP registry
When implementing an MCP registry, organizations have two options: either use a public MCP registry or create a private self-hosted MCP registry. According to the experts, there are trade-offs between each approach.
“A public MCP registry has to be very well evaluated for possible security risks before use,” says Melissa Ruzzi, director of AI at AppOmni, a cybersecurity company. Private registries are generally safer, she says, but the degree of risk depends on how they are implemented.
“The public registry ecosystem is still immature,” says Kevin Cochrane, CMO at Vultr, a cloud hosting provider. “We likely need a ‘Hugging Face for MCP’ — a trusted authority that can validate listings and set consistent standards.” Without that sort of layer, teams should be cautious about smaller third-party registries, he adds.
Instead, a private MCP registry can help an enterprise govern its portfolio. “Put a private MCP registry at the heart of the AI runtime,” Cochrane says. “This should be core infrastructure owned by platform engineering, with governance over how MCP servers are built, tested, deployed, and monitored.”
Infracodebase’s O’Connor adds that such curated registries engender trust in specific tools. “Over time, registries also become a trust boundary, especially in public settings, because they shape what tools people are willing to bring into workflows,” he says.
For many, the starting point will likely be a combination of both. This could equate to forking a sample open-source MCP registry and extending it to your needs.
“Another way is to take a published OpenAPI specification and generate a skeleton service implementation in a language of your choice,” says Andrei Denissov, associate director of software engineering at Cognizant AI Lab, the AI research arm for Cognizant.
Tips on building MCP registries
Experimentation with MCP registries is in its early days. However, developers on the front lines are already pulling out lessons learned and discovering patterns for both good and bad designs.
One lesson is the sheer realization that you need registries, quicker than you think. “Working with teams deploying MCP at an enterprise scale, the pattern is consistent: Registries become necessary faster than organizations expect,” says Ido Halevi, director of product management at Silverfort, an identity security company.
Then, those implementing MCP registries quickly learn that a basic MCP catalog is only one part of the picture — enterprises need much more than just MCP tool discovery. They need per-agent authorization models, guaranteed human-linked attribution, deep observability into agent behavior, and inline enforcement,” says Halevi.
When operating many MCP servers at scale, other requirements beyond discovery begin to become just as important, adds Halevi, such as MCP server orchestration, managing keys, keeping versions aligned, and managing configuration changes.
Balancing agentic autonomy and control
In the enterprise, sanctioned MCP use is proving to be incredibly powerful. Just take the case of Workato, which experienced a 700% increase in Claude chats from internal employees over a 60-day period when it turned on enterprise MCP features. Support engineers, financial analysts, sales leads, and others are building new workflows that grow Workato’s business in tangible ways, much in part thanks to MCP.
Getting those results, however, requires balancing agentic autonomy with control. That’s where an MCP registry can shine. For an enterprise, the quality of an MCP registry doesn’t just depend on listing every MCP server in a directory. It hinges on trust, safety, and smart controls — especially to prevent leaking data from chat streams across inter-organizational agent workflows, for instance.
As such, enterprises going “all in” on MCP should seriously consider MCP registries as a core infrastructure, with all the standard architectural enterprise bells and whistles. “It should be treated like any other serious piece of software,” says Alareqi. “That means strong versioning, life-cycle management, and observability.”
