AI is moving fast. And nowhere faster than MCP. Model Context Protocol (MCP) has quickly become a de facto element within today’s AI systems as the standard way to connect agents with external data, tools, and APIs.
Since its introduction in late 2024, MCP has progressed rapidly. Now, there are over 20,000 MCP servers. And according to statistics from PulseMCP, in May 2026 alone, developers downloaded 65 million local MCP servers across the entire internet. MCP servers are now being deployed across enterprise software engineering and are supporting new agentic business workflows too.
As adoption grows, so do the governance challenges. Enterprises now have to contend with conflicting authentication standards, shadow tool use, privilege drift, and emerging AI vulnerabilities. Without a unifying gateway to limit, route, and observe MCP-driven traffic, corporate environments risk technical sprawl and compliance problems. So what’s needed to scale MCP safely inside an enterprise?
An MCP gateway solves many of these issues. It acts as a central governance layer to handle authentication, curate MCP tool permissions, and observe MCP traffic across environments. Below, we cover the benefits an MCP gateway brings to enterprise architects and security leaders across business, technical, and security requirements.
- Enterprise architects standardizing how agents reach internal tools and APIs
- Security leaders enforcing least-privilege and zero-trust across MCP servers
- Platform teams governing the MCP servers employees already use
To enforce access policies
Using multiple MCP servers without a consistent access control policy is a recipe for fragmented security configurations. An MCP gateway fixes this with role-based access (RBAC) for upstream MCP tools, enforcing a least privilege policy that avoids permission drift and unintended exposure.
A gateway is the ideal layer to curate access to upstream tools and enforce OAuth policies project-wide. With a flexible MCP gateway like Zuplo’s, administrators can spin up virtual MCP servers: gateway-hosted servers that sit in front of the same upstream (the real MCP server behind the gateway) but expose their own auth and tool set. One upstream can back several access levels, such as read-only access for junior developers and partners or write privileges for senior engineers, as a configuration change rather than a separate deployment.
Most MCP gateways also integrate with your identity service provider (IDP), so an enterprise can keep its chosen identity solution, whether Microsoft Entra, Okta, or Auth0, to authenticate with upstream servers. The result is a centralized enforcement layer for standards-based authentication and zero-trust identity delegation.
MCP Gateway Quickstart
Build your first virtual MCP server in the browser: pick an upstream, wire up OAuth, curate the tools agents can see, and route every call through your analytics.
To handle all server types
As the industry shifts from the UI to agentic consumption for popular SaaS, large organizations are incorporating more and more MCPs from external sources. But not all upstream MCP servers are built the same way. Each has its own eccentricities, and many are not compliant with the latest MCP specification or security best practices.
Some popular MCP servers do not support OAuth and rely on API keys instead. For a security team trying to standardize on OAuth across the agents and servers it governs, that inconsistency is a headache, leading to a fractured MCP portfolio with hacky per-server workarounds to bridge the auth gap.
API keys are bad for security too: they are long-lived, poorly stored, over-permissioned, and routinely leaked. Token mismanagement and secret exposure is the top MCP vulnerability in OWASP’s MCP Top 10, and these factors create security gaps.
With an MCP gateway like Zuplo MCP Gateway, you can secure any MCP server, regardless of its core authentication mechanism. Security engineers can wrap a server that only supports API keys in OAuth: clients authenticate to the gateway with OAuth, and the gateway swaps in the upstream API key before forwarding the call. The result is a fully-compliant, secure server for internal use, with the long-lived key held by the gateway instead of scattered across clients.
To support compliance
Most large organizations juggle countless regulatory and corporate compliance requirements around data storage and access: SOC 2, GDPR, HIPAA, and more. If an agent accesses personally identifiable information (PII) improperly, a company is exposed to hefty fines and consumer lawsuits.
An MCP gateway supports data compliance by giving you visibility into who’s making calls, how they behave, and which departments or users call most. Logging and analytics produce a detailed audit trail of MCP use that informs an enterprise’s data posture.
With a gateway like Zuplo, you can also position any MCP server for highly regulated environments and private clouds: generate an MCP server for internal use, keep all traffic on a private, secured path, and provide OAuth-based access. Developers then collaborate on a completely internal, secure server.
To guide capability discovery
Agentic systems are interfacing with a ballooning number of MCP servers. The Zuplo State of MCP Report found that 70% of MCP consumers already have between 2 and 7 servers configured, and most expect that to increase. Without proper documentation, semantics, and discovery controls, agents are left guessing which API endpoints to call or methods to use, resulting in confusion and hallucination.
MCP gateways provide a catalog or registry to document all approved servers, aiding service discovery. It aggregates sanctioned technology and decreases the likelihood of rogue MCP servers, a new form of shadow IT.
A gateway can go beyond basic discovery with capability filtering: serving only the tools, prompts, and resources within a server tailored to whoever is using it. That lets you build highly-relevant agentic capabilities matched to the engineering context, role, or domain in question.
Capability filtering avoids information overload. Every tool definition an agent sees is injected into the model’s context window and costs tokens, so trimming the list to what a role actually needs cuts both LLM confusion and token bloat. Within Zuplo’s MCP Gateway, this filtering can be configured with code or UI and served as a pre-packaged MCP server for clients to consume.
To centralize on a source of truth
About half of MCP servers are wrappers around pre-existing APIs, per The State of MCP Report. The research also found that, much like the ubiquity of API gateways, using a gateway is the top emerging method to host an MCP server. So a gateway serves a double purpose: governing access to upstream servers and hosting your own servers for external consumers.
Many MCP servers are built directly from an OpenAPI specification. Zuplo API gateway users can generate MCP servers from their specification-defined API, then add a virtual MCP server on top to enable custom tooling access for public, internal, or partner consumers, all within the same project and all using the same OpenAPI specification as a source of truth.
Centralizing corporate interfaces this way is table stakes for enterprise governance, which often dictates strict specification-driven documentation practices. A multi-purpose gateway that supports APIs alongside MCP servers is also a boon for unified governance and ongoing management.
To limit AI security threats
Beyond MCP sprawl and access control, large language models (LLMs) carry their own security risks. LLMs are non-deterministic and behave in unpredictable ways, which exacerbates MCP risks and makes the case for an enterprise MCP gateway even clearer.
OWASP’s top ten list for LLMs ranks vulnerabilities like prompt injection, data and model poisoning, and improper output handling as common risks in generative AI systems. An MCP gateway responds by acting as a control layer to observe MCP tool call behavior and alert security teams to insider threats or malicious abuse.
A gateway also helps with other OWASP risks tied to how much access an agent has, including excessive agency (an agent able to take more actions than the task needs), system prompt leakage, and unbounded consumption. By scoping what capabilities an agent’s LLM can reach and what write functions it has, enterprises can sharply limit these emerging attack vectors.
Additional MCP gateway benefits
Beyond stronger access and security controls, an MCP gateway benefits a large organization in other ways:
- Reduce costs: gateways can enforce usage policies that prevent high-volume tool calls, oversized payloads, and excessive resource consumption, all of which drive token drain and cost overruns.
- Document chained workflows: some gateways let you define workflows that span multiple MCP servers, cementing common multi-step operations.
- Aid model agnosticism: some gateways include LLM API routing, acting as a unified AI gateway that lets agents switch underlying LLMs more easily.
MCP gateways aid enterprise agentic governance
A new level of productive agentic business is within reach. With MCP-enabled access to external systems and data, the LLMs developers command get the context and capabilities they need to push innovation into new territory.
But MCP use needs governance. As developers give autonomous agents more power via MCP, the blast radius expands, and with it the ability for agents to cause real harm. Take the PocketOS incident, in which an agent deleted an entire company’s database: a vivid example of what agents can do without proper guardrails.
An MCP gateway curbs exactly this class of overpermissioned access. Hand an agent a virtual server scoped to read-only tools and there is no destructive write for it to reach for, no matter how the model behaves. Centralized control over MCP access is critical to prevent data leakage and keep a least-privilege, zero-trust model across an organization, especially for teams scaling MCP use company-wide.
A number of MCP gateways, like Zuplo MCP Gateway, are emerging to provide these capabilities at scale. From an enterprise security governance perspective, they are worth considering as a way to both leverage MCP-driven innovation and curtail the risks of AI agents.