Best MCP Gateways for Enterprises in 2026

Model Context Protocol (MCP) has moved from a developer experiment to a production-critical standard at a striking pace. As AI agents proliferate across enterprise environments, the question is no longer whether to deploy MCP, but how to do it safely at scale. Running MCP servers directly in production works for prototypes. At enterprise scale, that approach surfaces three hard problems: unmanaged permissions, zero observability, and fragmented credential management.

MCP gateways solve these problems by sitting between AI agents and the tools they call, centralizing authentication, enforcing access policies, and capturing every tool invocation in a structured audit trail. This guide evaluates five of the strongest options for enterprise teams in 2026.

What to Look for in an Enterprise MCP Gateway

Before comparing specific products, it helps to define the evaluation criteria that actually matter for production deployments.

• Security and authentication: support for OAuth 2.1 (added to the MCP specification in June 2025), RBAC at the tool level, and integration with enterprise identity providers (Okta, Entra ID/Azure AD)
• Audit and compliance: immutable logs sufficient for SOC 2, HIPAA, and GDPR requirements
• Transport support: STDIO, HTTP, and SSE coverage; gateways that only support remote HTTP/SSE limit access to the majority of community-built MCP servers
• Performance: latency overhead per request at production throughput levels
• Observability: structured metrics, distributed tracing, and integration with existing monitoring stacks
• Governance controls: per-consumer rate limits, budget caps, and tool filtering without code changes

With those criteria established, here is how five leading MCP gateways compare.

1. Bifrost

Best for: Enterprises that need production performance, open-source transparency, and unified LLM and MCP infrastructure in a single gateway

Bifrost is an open-source, Go-native AI gateway built by Maxim AI that functions as both an MCP client (connecting to external tool servers) and an MCP server (exposing tools to clients like Claude Desktop and Cursor) through a single deployment. That dual-role architecture means teams manage one gateway for both LLM routing and MCP tool execution, rather than two separate infrastructure layers.

The Bifrost MCP gateway adds 11 microseconds of internal overhead at 5,000 requests per second. That is not a theoretical benchmark number: the performance benchmarks show sustained throughput figures at that overhead in realistic workload conditions.

Security architecture

Bifrost's default posture is stateless with explicit approval. Tool calls from LLMs are suggestions, not automatic actions. Execution requires a separate API call from the application, giving teams a clear enforcement point before any tool runs. For enterprises in regulated industries, this design eliminates an entire class of risk around unintended data modification or API calls.

For teams that need autonomous execution, Agent Mode provides configurable auto-approval: teams specify exactly which tools can auto-execute while maintaining human oversight for sensitive operations.

Governance and access control

Bifrost's governance model centers on virtual keys. Each virtual key carries its own rate limits, budget caps, and tool filtering rules, which means different teams, agents, or deployment environments can have distinct tool access policies without code changes. Per-key tool filtering lets administrators blacklist specific tools globally or restrict tool sets per consumer.

Enterprise deployments also get MCP with federated auth, which transforms existing internal APIs into MCP tools without requiring any code modifications to those services. For organizations with large inventories of internal APIs, this significantly reduces the onboarding cost of making those services agent-accessible.

Performance: Code Mode

Bifrost introduces Code Mode as an alternative to classic MCP tool calling for workloads using three or more MCP servers. Instead of injecting all tool schemas into every LLM request (which scales poorly with server count), the AI writes Python to orchestrate tools in a sandboxed environment. The result: 50% fewer tokens consumed and 40% faster execution compared to sequential tool calls.

Compliance

Audit logs capture every tool suggestion, approval, and execution with full metadata. The logging pipeline is designed for SOC 2, GDPR, HIPAA, and ISO 27001 requirements. Native OpenTelemetry export and a Datadog connector cover observability requirements for teams already invested in existing monitoring infrastructure.

Bifrost is open source under Apache 2.0, available on GitHub, with enterprise support available through Maxim AI. The LLM Gateway Buyer's Guide covers how Bifrost compares across gateway dimensions in more depth.

2. IBM Context Forge

IBM Context Forge is an open-source MCP gateway, proxy, and registry that approaches the problem from a federation-first angle. Where most gateways assume a single control point, Context Forge is designed for organizations running multiple MCP gateway instances across environments or regions that need to work together as a unified system.

Auto-discovery via mDNS, health monitoring, and capability merging allow multiple Context Forge gateways to detect each other and surface a combined tool catalog to agents, without manual configuration of inter-gateway routing. Virtual server composition lets teams combine multiple MCP servers into single logical endpoints, which simplifies how agents discover and call tools without exposing backend complexity.

Authentication supports JWT bearer tokens, Basic Auth, and custom header schemes, with AES encryption for tool credentials at rest. Multi-database connectors for PostgreSQL, MySQL, and SQLite make it practical to expose existing enterprise data sources as MCP tools without custom middleware.

The main adoption constraint is support posture: IBM Context Forge carries an explicit disclaimer that it does not have official IBM commercial support. For enterprises that require vendor SLAs and dedicated escalation paths, this is a meaningful operational risk. Teams considering it should have strong internal infrastructure expertise and be comfortable treating it as a community project rather than a commercially backed product.

3. Kong AI Gateway (MCP Proxy)

Kong added MCP capabilities in AI Gateway version 3.12 (October 2025) through an MCP Proxy plugin, OAuth 2.1 support aligned with the June 2025 MCP specification, and MCP-specific Prometheus metrics. For organizations already operating Kong as their API management layer, this is a natural consolidation move: MCP policies sit alongside existing API gateway policies in a familiar control plane.

The governance capabilities are solid: centralized policy enforcement, OAuth 2.1 as Resource Server, and integration with Kong Konnect's existing traffic management. The observability story (Prometheus metrics, integration with existing dashboards) is strong for teams that have already built around Kong's metrics pipeline.

The tradeoff is that Kong's MCP support is not native to MCP architecture. It was added to a mature API gateway product, which means teams greenfield on MCP will pay for API gateway capabilities they may not need. Enterprise licensing for Kong runs above $50,000 per year, which warrants scrutiny if MCP governance is the primary use case.

4. Lunar.dev MCPX

MCPX is Lunar.dev's MCP gateway, built around enterprise governance and security monitoring rather than raw throughput. Its integration with Lunar's broader AI Gateway enables end-to-end traffic inspection across both LLM calls and tool invocations, which matters for organizations that need a single audit record spanning the full agent workflow.

The access control model is granular: ACLs can be defined at global, service, or individual tool level. Tool scoping and parameter overrides allow administrators to create restricted variants of tools that enforce approved parameter ranges, reducing the surface area for misuse. The private deployment option supports on-premises and VPC deployments for data sovereignty requirements.

MCPX's performance profile reflects its priorities: the overhead is higher than Bifrost, which is an acceptable trade-off for regulated financial services, healthcare, or government use cases where compliance depth outweighs raw latency.

5. Docker MCP Gateway

Docker's MCP Gateway applies container orchestration principles to MCP server management. Each MCP server runs in an isolated container with CPU and memory limits, and images are cryptographically signed for supply-chain security. Dynamic server registration and a single unified endpoint give agents consistent tool discovery regardless of how many servers are running in the background.

The secrets management layer and container isolation model are well-suited for teams that already reason about security through container primitives. Docker Desktop integration simplifies local development setup, which reduces the gap between development and production environments for teams already in Docker's ecosystem.

Docker's MCP Gateway is a strong fit for container-native infrastructure teams, particularly those executing code in agent workflows where container-level isolation provides meaningful security boundaries. For teams not already invested in container orchestration, the operational overhead of managing container workloads adds friction that purpose-built MCP gateways avoid.

Comparing the Five Options

What an enterprise MCP setup looks like with Bifrost

The work that turns "we connected MCP servers" into "we run MCP in production" happens at the gateway layer. Start Bifrost locally:

npx -y @maximhq/bifrost

Connect each MCP server in the dashboard at http://localhost:8080, configure virtual keys for each team or agent, and apply per-tool access policies. Every agent in the organization gets one endpoint, one auth flow, and one observability surface. Adding a new MCP server later is a config change at the gateway, not a deployment across every agent.

Three things matter most for enterprise deployments:

• OAuth 2.1 lives at the gateway. The June 2025 MCP spec update made OAuth 2.1 the production-grade default. Each individual MCP server doesn't need to handle SSO directly; Bifrost sits between the agent and the identity provider, handling token issuance, refresh, and propagation downstream. The Claude Code integration covers the auth flow end-to-end.
• Virtual keys give per-team accountability. A single physical provider key can map to dozens of virtual keys, each with its own rate limit, tool allow-list, and audit trail. When the security team asks "who triggered this tool call last Tuesday," the answer is in the gateway logs, attributed to the virtual key (and therefore to the team or agent that owns it). The provider status feed tracks gateway-level health alongside upstream provider health.
• Token reduction compounds with tool count. Code Mode addresses the context overhead problem at the schema-injection layer rather than the request layer. A typical enterprise running ten MCP servers with thirty tools each is putting 300 tool definitions in front of the model on every request without it. With Code Mode, definitions get fetched on-demand. Full benchmark methodology is in the Bifrost MCP benchmark report.

For teams comparing gateways at the procurement stage, the LLM gateway buyer's guide covers the criteria that matter at production scale.

Get Started with Bifrost

Bifrost's MCP gateway is available as open source on GitHub. For enterprise deployments requiring clustering, federated authentication, advanced guardrails, and dedicated support, book a demo with the Bifrost team.