Top 5 MCP Gateways for Claude in 2026

Claude supports Model Context Protocol natively across Claude Code, Claude Desktop, and Claude Web. Connect a filesystem server, a GitHub integration, and a database tool, and Claude can act on all three from the same session. The protocol works as advertised. The operational problem emerges when the tool count grows.

Every MCP server you connect to Claude loads its tool definitions into the context window before Claude processes a single token of your actual request. One developer measured 15,540 tokens consumed at session start across 84 tools from several connected servers, before the agent had processed a single user message. At team scale, with multiple developers sharing configurations and 10+ servers each exposing 15-20 tools, the token overhead becomes a significant cost and latency problem.

An MCP gateway sits between Claude and your tool servers, exposing everything through a single endpoint. Claude connects once. The gateway handles discovery, routing, authentication, and tool filtering centrally. This guide evaluates five MCP gateways on the dimensions that matter most for Claude deployments: token efficiency, Claude-specific integration depth, security controls, and production readiness.

What Makes an MCP Gateway Work Well with Claude

Claude's MCP implementation has a few characteristics that determine how well a gateway fits:

• Transport support: Claude Code supports HTTP and stdio. Claude Desktop uses stdio. Claude Web uses remote HTTP with OAuth. A gateway that only handles one transport limits which Claude surfaces you can use it with.
• Tool filtering: Claude loads all tools from all connected servers into context. A gateway that controls which tools are visible per consumer directly reduces prompt overhead, not just as a governance feature but as a cost control.
• OAuth 2.1: Added to the MCP specification in June 2025, OAuth 2.1 is increasingly required for enterprise-grade Claude deployments. Gateways that implement it properly let Claude Web and Claude Code authenticate cleanly against enterprise identity providers.
• Single gateway URL: Claude's configuration model handles one connection per server entry. A gateway that exposes all tools through a single URL keeps Claude's config simple as your tool inventory grows.

With those criteria established, here is how five MCP gateways compare for Claude deployments.

1. Bifrost

Best for: teams using Claude Code or Claude Desktop who need enterprise-grade MCP governance, token efficiency via Code Mode, and a single gateway that handles both LLM routing and MCP tool management

Bifrost is an open-source, Go-native AI gateway by Maxim AI that functions as both an MCP client and an MCP server simultaneously. For Claude deployments specifically, this dual-role architecture means Claude connects to one Bifrost endpoint and immediately sees all tools from all connected MCP servers, filtered and governed by policy.

Connecting Claude Code to Bifrost takes a single command:

claude mcp add --transport http bifrost <http://localhost:8080/mcp>

From that point forward, Bifrost handles all tool discovery, authentication, and execution. Adding new MCP servers to Bifrost makes them available in Claude Code automatically with no client-side config changes.

The Bifrost Claude Code integration also supports routing Claude Code's underlying model through Bifrost's LLM gateway, which means Claude Code can switch to GPT-4o, Gemini, or any of 20+ configured providers without changing the CLI or codebase. This matters for enterprise teams that need model flexibility or cost-based routing alongside MCP tool management.

Token efficiency: Code Mode

Bifrost's Code Mode addresses the context-window overhead problem directly. Instead of injecting all tool schemas into every request, the model writes Python to orchestrate tools in a sandboxed environment. Four meta-tools replace 100+ definitions, and on-demand schema loading means the model only retrieves the schema for a tool it has actually decided to use. The result is 50% fewer tokens consumed and 40% faster execution compared to classic tool calling across multiple servers.

For Claude Code sessions working against large codebases where context is already at a premium, this is a material improvement.

Per-consumer tool filtering

Bifrost's tool filtering scopes which tools are visible per virtual key. A developer working on frontend tasks gets access to filesystem and GitHub tools. A data analyst gets database query tools. Neither sees the other's tool definitions, which means neither bears the token cost of irrelevant schemas. The model never receives definitions for tools outside its scope, so there is no prompt-level workaround.

Security and compliance

Bifrost's default execution model is stateless with explicit approval: tool calls from Claude are suggestions, not automatic actions. Agent Mode enables autonomous execution for approved tools when needed, with configurable auto-approval lists. OAuth 2.0 authentication with automatic token refresh handles enterprise identity provider integration.

The full MCP Gateway architecture is documented on the Bifrost MCP Gateway resource page, including transport configurations, Code Mode setup, and deployment options.

Bifrost is open source under Apache 2.0 on GitHub, with enterprise features including clustering, federated authentication, and dedicated support available through Maxim AI.

2. Cloudflare MCP

Best for: teams already running workloads on Cloudflare's network that want a managed, globally distributed MCP layer without operating gateway infrastructure themselves

Cloudflare's MCP support, built into its Workers and AI Gateway products, enables teams to expose MCP servers over Cloudflare's edge network. The primary advantage is geographic distribution: requests from Claude route to the nearest Cloudflare point of presence, which reduces latency for global teams. Cloudflare handles TLS termination, DDoS protection, and basic access control at the edge.

The integration model is familiar to teams already on Cloudflare. MCP servers deployed as Cloudflare Workers use Cloudflare's existing secrets management and routing infrastructure. OAuth 2.1 support ships with Cloudflare's standard auth primitives. For teams where Cloudflare already manages API traffic, extending that infrastructure to cover MCP reduces the number of distinct systems to operate.

The main constraint for enterprise Claude deployments is governance depth. Cloudflare's MCP capabilities provide connectivity and basic security controls, but the per-consumer tool filtering, hierarchical budget management, and Code Mode token optimization that matter for large-scale Claude Code deployments require additional tooling. It is a strong fit for connectivity-first requirements; teams that need deep governance will need to layer additional controls.

3. Composio

Composio offers a managed MCP gateway with integrations for over 1,000 pre-built tools covering SaaS applications, databases, APIs, and developer services. For Claude Code deployments where the primary need is connecting to a wide range of third-party services quickly, this breadth reduces the integration work significantly compared to configuring individual MCP servers.

The managed service model means Composio handles MCP server infrastructure, authentication flows, and tool updates. For teams without a dedicated platform team to operate gateway infrastructure, this lowers the operational burden of deploying MCP at scale. Tool definitions stay current with upstream API changes without requiring teams to maintain their own server configurations.

Composio's tradeoff is the inverse of self-hosted gateways: breadth of integrations and low operational overhead, at the cost of reduced control over execution, compliance posture, and per-request governance. For regulated industries requiring in-VPC deployment, SOC 2-compliant audit logs, or per-virtual-key budget enforcement, a self-hosted gateway gives teams controls that a managed service cannot replicate. Teams not subject to those constraints will find Composio's tool library and managed reliability compelling.

4. Kong AI Gateway

Kong added an MCP Proxy plugin in AI Gateway version 3.12 (October 2025), alongside OAuth 2.1 support and MCP-specific Prometheus metrics. For organizations already operating Kong as their API gateway, this provides a natural consolidation path: MCP policies coexist with existing API gateway policies in a familiar control plane, and observability data lands in the same monitoring stack.

Kong's enterprise governance capabilities apply to MCP traffic the same way they apply to API traffic: rate limiting per consumer, policy enforcement, and centralized authentication. The Prometheus metrics integration is particularly useful for teams that have already built LLM cost and latency dashboards in Grafana or Datadog and want to extend them to cover MCP tool invocations.

The constraint for teams evaluating Kong specifically for Claude's MCP workloads is that Kong is not MCP-native. MCP support was added to a mature API management product, which means the tool-level filtering, Code Mode token optimization, and Claude-specific integration depth available in purpose-built MCP gateways are not present. Teams already invested in Kong's ecosystem will find the consolidation worth it. Teams evaluating MCP infrastructure from scratch will pay for API management capabilities they do not need.

5. Docker MCP Gateway

Docker's MCP Gateway applies container orchestration principles to MCP server management. Each server runs in an isolated container with CPU and memory limits, and images are cryptographically signed for supply-chain security. A single unified endpoint aggregates all servers, so Claude connects once regardless of how many containerized MCP servers are running in the background.

The isolation model provides meaningful security properties for specific Claude use cases: any MCP server that executes code, writes to a filesystem, or interacts with a database runs in a container that cannot affect other servers or the host system. For Claude Code deployments in engineering environments where agents are running scripts and modifying files, container-level isolation sets a clear security boundary around each tool.

Docker Desktop integration simplifies local development setup, which reduces the gap between how developers run Claude Code locally and how it runs in production. For teams already operating container infrastructure, this familiarity is a real operational advantage. Teams not already in Docker's ecosystem will encounter container orchestration overhead that purpose-built MCP gateways avoid.

Comparing the Five for Claude Deployments

How to Choose for Claude

The right gateway depends primarily on where your Claude deployment is running and what your primary constraint is.

Choose Bifrost if Claude Code or Claude Desktop is your primary agent surface, you need enterprise governance (tool filtering, budget controls, audit logs), and token efficiency across multiple MCP servers matters. It is also the only option here that handles both LLM routing and MCP tool management in a single gateway, eliminating the need for separate infrastructure layers.

Choose Cloudflare if global latency distribution is the primary requirement and your team is already running workloads on Cloudflare's network.

Choose Composio if time-to-first-integration matters most and your use cases map to the pre-built tool library, and you are not subject to compliance requirements that demand self-hosted infrastructure.

Choose Kong if MCP governance needs to sit inside an existing Kong deployment rather than introducing a separate infrastructure layer.

Choose Docker if Claude agents are executing code or performing filesystem operations and container-level isolation is a non-negotiable security requirement.

Get Started with Bifrost for Claude

Bifrost's Claude Code integration and full MCP gateway are available open source on GitHub. For enterprise deployments with clustering, federated authentication, advanced guardrails, and dedicated support, book a demo with the Bifrost team.