Top MCP Gateway Solutions for GenAI Builders

Compare leading MCP gateway solutions and understand how they differ across authentication, access control, policy enforcement, and operational readiness for production AI systems.

What is an MCP Gateway?

An MCP gateway is a centralized control layer that sits between AI agents, applications, and MCP servers. Instead of agents connecting directly to MCP servers and tools, all MCP traffic flows through the gateway. This allows teams to enforce consistent authentication, access control, and policies across every MCP interaction.

Core functions of an AI gateway

Authentication and identity handling

It authenticates agents and applications before they can interact with MCP servers, removing the need for each MCP server to implement its own auth logic.

Authorization and access control

The gateway enforces authorization policies that determine which MCP servers, tools, and resources each agent or team is allowed to use across environments.

Policy enforcement at the network layer

Policies are enforced at the network layer as MCP traffic flows through the gateway, eliminating the need to embed security and governance logic inside agents or MCP servers.

Observability

The gateway provides organization-wide observability into MCP usage, including which agents invoke which tools, how often, and under what conditions.

Why teams need an MCP gateway

MCP adoption often begins with direct connections between agents and tools, which quickly becomes difficult to manage as usage spreads across teams and environments.

Without a gateway, MCP servers are accessed inconsistently, making it hard to control who can use which tools and under what conditions.

The production challenges

Fragmented authentication

Each MCP server implements its own authentication mechanism, making identity management inconsistent and difficult to audit.

Inconsistent authorization

Access rules vary by server and tool, leaving teams without a reliable way to define who can use what across the organization.

Limited visibility and auditing

Teams cannot easily trace which users accessed which tools, how frequently, or where failures occur.

Governance gaps

There is no unified way to enforce organization-wide policies, audit MCP usage, or support compliance requirements.

Operational complexity

Managing MCP access, credentials, and policies across multiple agents and environments quickly becomes brittle as systems grow.

In-Depth Analysis of the Top MCP Gateways

Dive deeper into each solution, covering their core strengths, weaknesses, pricing, customer base, and market reputation, to help teams choose the right gateway for their GenAI production stack.

Portkey

Portkey's MCP gateway is designed to help teams adopt MCP in production with centralized access control, policy enforcement, and observability. It provides a managed control plane to register MCP servers, govern tool access across teams, and monitor MCP usage across teams.

Strengths

Centralized authentication and authorization

Enforces consistent identity and access policies at the gateway layer instead of distributing auth logic across users and servers. Supports OAuth and SSO/IAM integrations for enterprise identity providers.

Managed MCP server registry

Provides a controlled inventory of approved MCP servers, reducing accidental exposure and tool sprawl.

Enterprise governance capabilities

Supports role-based access control and access control lists at global, service, and tool levels, allowing permissions to be scoped precisely per user or workspace.

Production observability

Offers request-level visibility into MCP activity to support debugging, monitoring, and operational oversight.

Single control panel for LLMs and MCP

Manages LLM access and MCP server usage through a single control layer, allowing teams to apply consistent policies, routing, and governance across both.

Pricing Structure

Portkey follows a managed SaaS model with usage-based pricing and enterprise plans for advanced governance and organizational controls.

Ideal For / Typical Users

• Platform and infrastructure teams standardizing MCP across multiple teams or products.
• Organizations that require centralized governance, visibility, and auditability for MCP usage.
• Teams moving MCP from experimentation into production without building and maintaining a gateway in-house.

Lunar.dev

Lunar.dev’s MCPX is an enterprise-focused MCP gateway that provides governed access to multiple MCP servers, with fine-grained permissions, deployment flexibility, and compliance for regulated environments.

Strengths

Fine-grained authorization controls

Offers RBAC and ACLs with global, service, and tool-level scoping for agent access control.

Enterprise authentication options

Provides API key and OAuth-based authentication for MCP access, along with SSO and IAM integrations for enterprise identity providers.

Flexible deployment models

Can be deployed as a managed service, in a customer’s cloud, or on-premises, supporting data residency and sovereignty requirements.

Tool customization and scoping

Allows modification of tool descriptions and parameter constraints to create safer, scoped tool variants for agent usage.

Pricing Structure

Lunar.dev typically follows a SaaS pricing model oriented around usage and traffic volume, with enterprise plans available for larger deployments.

Ideal For / Typical Users

• Teams primarily focused on reliability, retries, and traffic management for AI or MCP requests.
• Organizations looking to extend existing gateway patterns to MCP without introducing a dedicated MCP control plane.
• Smaller teams or early-stage deployments where governance requirements are minimal.

IBM MCP Gateway

IBM’s MCP Gateway is positioned as an enterprise MCP access layer designed to support governed AI workflows within the IBM ecosystem, with a focus on security, compliance, and integration with existing IBM platforms.

Strengths

Enterprise security alignment

Designed to meet enterprise security and compliance expectations, using IBM’s broader identity, security, and governance tooling.

Integration with IBM AI and data platforms

Works naturally within IBM’s AI stack, making it easier to adopt MCP in environments already standardized on IBM infrastructure.

Centralized access enforcement

Provides a single control point for managing access to MCP servers within IBM-managed deployments.

Pricing Structure

IBM MCP Gateway is typically offered under enterprise licensing or custom contracts, often bundled with broader IBM AI or cloud offerings.

Ideal For / Typical Users

Large enterprises already standardized on IBM infrastructure and security tooling.

Kong

Kong’s MCP Gateway is a part of their larger AI Gateway offering and is an enterprise-only solution that leverages paid plugins.

Strengths

Centralized MCP authentication

Uses a dedicated MCP authentication plugin to act as a central OAuth 2.1 resource server, validating tokens and enforcing uniform security policies across both auto-generated and existing MCP servers.

Discoverable MCP services for agents

Allows MCP servers to be published as discoverable, self-serve products through a service catalog and developer portal, reducing onboarding friction for teams building agentic workflows.

Monetization and usage management

Enables organizations to track, govern, and potentially monetize MCP and API-driven services through centralized policy and usage controls.

Use APIs as MCP servers

Use any existing Kong-managed REST API and generate a remote MCP server (hosted by Kong) that can be accessed by agents, AI coding tools, and other AI applications.

Pricing Structure

Kong offers open-source and enterprise editions, with enterprise pricing based on deployment scale, features, and support requirements.

Ideal For / Typical Users

• Organizations already using Kong as their standard API gateway.
• Platform teams comfortable extending gateway behavior through custom plugins.
• Enterprises prioritizing traffic control and deployment flexibility over MCP-native abstractions.

TrueFoundry

TrueFoundry is an ML and AI platform that includes MCP support as part of a broader platform for deploying, operating, and governing AI systems.

Strengths

Aligned with ML and platform teams

Fits naturally into organizations that already use TrueFoundry as their primary ML or AI platform.

Low-latency request handling

Handles authentication and rate limiting in memory, enabling sub-3 ms latency under load for MCP requests.

Integrated infrastructure controls

Includes rate limiting, load balancing, guardrails, and unified billing as part of the MCP gateway, reducing the need for external components.

Logical isolation via MCP server groups

Supports grouping of MCP servers to provide isolation across teams or use cases within the same deployment.

Pricing Structure

TrueFoundry typically offers enterprise pricing based on platform usage, infrastructure scale, and support requirements.

Ideal For / Typical Users

• Organizations standardized on TrueFoundry’s AI infrastructure platform.
• Platform teams comfortable operating containerized, infrastructure-heavy AI systems.

Microsoft MCP Gateway

Microsoft’s MCP Gateway is positioned as a cloud-native access layer for MCP servers within the Azure ecosystem, designed to align MCP usage with existing Azure identity, security, and governance primitives.

Strengths

Native alignment with Azure identity and security

Leverages Azure Active Directory, managed identities, and Azure security controls to handle authentication and authorization for MCP access.

Seamless fit within Azure AI workflows

Designed to work alongside Azure’s AI, agent, and platform services, reducing friction for teams already building on Azure.

Enterprise-grade compliance posture

Benefits from Azure’s compliance certifications and enterprise governance standards, making it suitable for regulated environments.

Centralized policy enforcement

Allows organizations to apply consistent access policies across MCP servers using familiar Azure governance constructs.

Pricing Structure

Microsoft MCP Gateway is typically priced as part of Azure service usage, with costs tied to underlying Azure resources, networking, and security components.

Ideal For / Typical Users

• Organizations standardized on Azure for AI, identity, and infrastructure.
• Platform teams extending existing Azure governance models to MCP-based workflows.

Key Capabilities of MCP Gateways

Authentication and identity management

Establish a consistent identity layer for users, agents or applications accessing MCP servers

Fine-grained access control

Set precise permissions for MCP servers, tools, and resources, scoped by agent, role, team, or environment.

MCP and tool registry

Maintain an approved inventory of MCP servers and tools, for easier discovery and access control.

Policy enforcement

Applies organization-wide rules such as usage limits, security controls, and restrictions as MCP traffic flows through the gateway.

Unified access layer

Get a single control plane to manage both LLM and MCP server usage within the same operational framework.

Operational simplicity

Reduce operational overhead by centralizing tool access, policy enforcement, and visibility across MCP deployments.

Why Portkey is different

Governance at scale

Built for enterprise control from day one

• Workspaces and role-based access
• Budgets, rate limits, and quotas
• Data residency controls
• SSO, SCIM, audit logs

HIPAA

COMPLIANT

GDPR

MCP-native capabilities

Portkey is the first AI gateway designed for MCP at scale. It provides:

• MCP server registry
• Tool and capability discovery
• Governance over tool execution
• Observability for tool calls and context loads
• Unified routing for both model calls and tool invocations

Comprehensive visibility into every request

• Tool calls
• Token usage and costs
• Latency
• Transformed logs for debugging
• Workspace, team, and model-level insights
• Error clustering and performance trends

Authentication and identity management

Supports OAuth, tokens, and JWT-based authentication for connecting MCP servers, enabling flexible identity models across environments.

Built-in policy enforcement

• PII redaction
• Jailbreak detection
• Toxicity and safety filters
• Request and response policy checks
• Moderation pipelines for agentic workflows

Server and tool catalog + provisioning

Provides a managed catalog for MCP servers and tools, with controlled provisioning and exposure instead of ad hoc discovery.

Reliability automation

Sophisticated failover and routing built into the gateway:

• Fallbacks and retries
• Canary and A/B routing
• Latency and cost-based selection
• Provider health checks
• Circuit breakers and dynamic throttling

Integrations

• Open AI

• Anthropic

• Google

• Azure Foundry

• Bedrock

• Nebius

• X AI

• Fireworks AI

Frequently Asked Questions

Some questions we get asked the most

Do I need an MCP gateway if I already control tool access in my agents?

How does an MCP gateway handle authentication and authorization?

Can an MCP gateway work with multiple MCP servers and tools?

How does an MCP gateway relate to LLM gateways or AI gateways?

Is Portkey SOC-compliant and enterprise-ready?

Portkey is a comprehensive platform designed to streamline and enhance AI integration for developers and organizations.