A single MCP server can give an AI agent read/write access to your production database, your CRM, your file system, and your Slack workspace. Multiply that by the 17,000+ MCP servers now indexed across public registries, and you have a tool discovery problem and a tool governance problem. MCP registries solve the first. MCP gateways solve the second. Most enterprises need both, and confusing them is how agent tool sprawl starts.
The registry is the catalog: it tells agents which tools exist, what they do, and how to connect. The gateway is the checkpoint: it sits between agents and MCP servers, enforcing authentication, authorization, rate limits, and audit logging before any request reaches a backend system. Think of the registry as your company’s internal app store and the gateway as the security guard at the data center door.
What an MCP Registry Actually Does
The official MCP Registry, launched in preview by the Model Context Protocol team in September 2025, works like a package manager for MCP servers. Developers publish server metadata (capabilities, version, transport type, authentication requirements) and clients query the registry API to discover available tools at runtime. No more hardcoding server URLs into agent configurations.
The registry follows three design principles that matter for enterprise use. First, it is vendor-neutral: governed under the Agentic AI Foundation (Linux Foundation), with Anthropic, Google, Microsoft, and OpenAI as members. Second, it supports both public and private instances, so companies can run internal registries with only approved servers visible. Third, it exposes a REST API with cursor-based pagination, making programmatic integration straightforward.
Public vs. Private Registries
The public registry is great for open-source discovery. But in production, you want a private registry where only vetted, company-approved MCP servers appear. This is exactly the model Kong’s MCP Registry (launched February 2026 as part of Kong Konnect) follows: a curated catalog within your existing API management platform, where servers inherit the same policy controls you apply to REST APIs.
ARegistry takes a broader approach, functioning as a centralized registry for all AI artifacts, including agents, MCP servers, skills, and models. Organizations import artifacts from any source, curate them through an approval workflow, and deploy to managed infrastructure.
The key distinction: public registries optimize for discovery. Private registries optimize for control. Enterprise deployments need both, typically using the public registry for initial server evaluation and a private registry for production deployment.
Server Discovery at Runtime
The MCP specification supports dynamic discovery through .well-known URLs, allowing servers to advertise their capabilities without clients connecting first. Combined with registry APIs, this means an agent can query “which MCP servers provide CRM access?” and get back a list of approved options with their connection details, authentication requirements, and version metadata, all without a developer manually configuring anything.
This sounds convenient. It is also the reason gateways exist: because convenience without control is how you end up with agents connecting to every MCP server that answers “yes” to a capability query.
MCP Gateways: The Control Plane for Agent Tool Access
An MCP gateway is an infrastructure layer that sits between AI agents and MCP servers, functioning as a reverse proxy with agent-aware security. Kong defines it as “a single, secure entry point for AI clients” that handles four jobs: protecting internal servers, enforcing authentication, routing requests intelligently, and providing centralized visibility.
The architecture is familiar if you have worked with API gateways. Requests flow from the agent through the gateway, which checks credentials, evaluates policies, logs the request, and then forwards it (or rejects it) to the appropriate MCP server. The difference is that MCP gateways understand agent-specific patterns: multi-step tool chains, session affinity across conversation turns, and tool-based routing where the gateway inspects the requested capability and directs traffic to the right backend.
Authentication and Authorization
Enterprise MCP gateways support OAuth 2.0, OpenID Connect (OIDC), and SAML for connecting agents to identity providers. But authentication alone does not solve the problem. You need authorization that accounts for what each agent is allowed to do.
This is where Role-Based Access Control (RBAC) and Attribute-Based Access Control (ABAC) come in. A customer service agent might have read access to the CRM but no write access to financial systems. A code review agent might interact with GitHub but never touch production deployment tools.
Strata’s Maverics AI Identity Gateway goes further with ephemeral, task-scoped tokens: instead of granting an agent standing access to a tool, the gateway mints short-lived tokens that expire after the specific task completes. An embedded Open Policy Agent (OPA) engine evaluates fine-grained policies at request time, considering not just the agent’s role but the current execution context.
Rate Limiting and Cost Control
Agents operate at machine speed. Without guardrails, a single runaway agent can exhaust API quotas, rack up cloud bills, or hammer a backend service into a denial-of-service state. MCP gateways enforce rate limits per agent, per tool, and per time window. Role-based profiles can set budget constraints, so your intern’s experimental agent cannot burn through $10,000 in OpenAI API calls overnight.
Audit Logging and Compliance
Every tool invocation that passes through the gateway gets logged: which agent called which tool, with what parameters, at what time, and what the response was. This is not optional for regulated industries. MintMCP’s gateway holds SOC 2 Type II certification, which means their audit trail controls have been independently verified for security, availability, and confidentiality. For GDPR compliance, gateways can enforce EU data residency requirements and provide the complete audit trails that Article 30 demands.
Seven MCP Gateways Compared
The market went from two options in late 2025 to a crowded field in early 2026. Here is what matters across the leading platforms.
Kong AI Gateway integrates MCP server management into Kong Konnect, the platform already handling API gateway duties for thousands of enterprises. Strength: you manage MCP servers alongside your existing APIs with inherited policy controls. Weakness: heavyweight for teams that only need MCP governance.
MintMCP Gateway is purpose-built for MCP with one-click STDIO deployment, OAuth/SSO protection, and SOC 2 Type II certification. Strength: fastest path from zero to governed MCP in production. Weakness: newer vendor, smaller ecosystem.
Strata Maverics approaches MCP governance through an identity fabric that federates MCP servers through your existing identity provider. Strength: ephemeral tokens and OPA-based policy engine. Weakness: primarily identity-focused; requires pairing with other tools for full observability.
Docker MCP Gateway leverages container-native infrastructure for teams already running Docker. Open-source (MIT license) with Kubernetes orchestration. Strength: zero vendor lock-in. Weakness: you build and maintain the governance layer yourself.
Lasso Security Gateway focuses on threat detection with a triple-gate security pattern across AI, MCP, and API layers. Real-time prompt injection detection and parameter validation. Strength: security-first for regulated industries. Weakness: less focus on developer experience.
Lunar.Dev MCPX offers centralized policy enforcement with RBAC and full request tracing. Supports both STDIO and remote HTTP/SSE servers. Strength: strong observability dashboard. Weakness: earlier stage than Kong or MintMCP.
Traefik Hub extends the popular Traefik reverse proxy with MCP middleware. OpenTelemetry integration for metrics. Strength: natural fit for teams already on Traefik. Weakness: MCP is an extension, not the core product.
Building an Enterprise MCP Governance Stack
A registry and a gateway together form the minimum viable governance layer for MCP in production. But getting from “we should govern our MCP servers” to actually doing it requires a practical plan.
Step 1: Inventory Your MCP Servers
Before you can govern anything, you need to know what exists. Run an audit of every MCP server connection across your organization. The Gravitee State of AI Agent Security 2026 survey found that only 14.4% of organizations have full security approval for all deployed agents. That means the other 85.6% have MCP servers running that nobody in security has reviewed.
Step 2: Deploy a Private Registry
Stand up an internal MCP registry (the official registry codebase is open-source on GitHub) or use a managed option like Kong’s Konnect Catalog. Populate it with approved servers only. Configure your agents to query this registry, not the public one, for tool discovery.
Step 3: Put a Gateway in Front of Everything
Route all MCP traffic through a gateway. Enforce OAuth/OIDC authentication, define RBAC policies per agent role, set rate limits, and enable audit logging. Start with a deny-by-default posture: agents can only access tools explicitly approved for their role.
Step 4: Monitor and Iterate
Use the gateway’s observability features to track tool usage patterns, identify unused servers (remove them), spot anomalous access patterns, and optimize rate limits based on actual consumption data.
The goal is not to slow agents down. It is to make ungoverned tool access impossible while making governed access fast and frictionless.
Frequently Asked Questions
What is the difference between an MCP registry and an MCP gateway?
A registry catalogs available MCP servers and helps agents discover which tools exist. A gateway controls access to those servers by enforcing authentication, authorization, rate limits, and audit logging. The registry answers “what tools can I use?” The gateway answers “are you allowed to use this tool right now?”
Do I need an MCP gateway if my agents only use internal tools?
Yes. Internal tools are often more sensitive than external ones (production databases, HR systems, financial data). A gateway ensures that even internal MCP server access is authenticated, authorized, logged, and rate-limited. Without one, any agent with network access can call any internal MCP server.
How does an MCP gateway handle authentication?
Most enterprise MCP gateways support OAuth 2.0, OpenID Connect, and SAML. They integrate with existing identity providers (Okta, Azure AD, Keycloak) so agents authenticate using the same infrastructure as human users. Advanced gateways mint ephemeral, task-scoped tokens that expire when the specific operation completes.
Which MCP gateway is best for regulated industries?
MintMCP holds SOC 2 Type II certification with auditor-verified controls. Lasso Security offers a triple-gate security pattern with real-time threat detection. Strata Maverics provides OPA-based policy enforcement with identity fabric integration. The right choice depends on whether your primary concern is audit compliance, active threat detection, or identity governance.
Can I use the official MCP Registry for private, internal use?
Yes. The official MCP Registry is open-source and designed to support both public and private instances. You can deploy your own registry that indexes only your company’s approved MCP servers, giving agents a curated catalog without exposing them to the full public registry.