5 Best MCP Gateways for Engineers and Developers in 2026

TL;DR

• An MCP gateway gives coding agents such as Claude Code, Cursor, and Codex CLI one endpoint for every MCP server, instead of a separate configuration per tool per client.
• The five best MCP gateways for developers in 2026 are Bifrost, Docker MCP Gateway, Composio, agentgateway, and MCPJungle.
• Bifrost connects Claude Code to every configured MCP tool with one claude mcp add command and routes the same agent's model traffic through one OpenAI-compatible gateway.
• Bifrost Code Mode reduced input tokens by 92.8% in a benchmark with 508 tools across 16 MCP servers, which directly shrinks the context a coding agent spends on tool definitions.
• Docker MCP Gateway fits container-based local development, Composio fits teams that want managed SaaS integrations, agentgateway fits Kubernetes platforms, and MCPJungle fits a lightweight self-hosted registry.

MCP gateways solve a problem most engineers hit within weeks of adopting AI coding tools: every MCP server has to be configured separately in Claude Code, Cursor, Codex CLI, and each custom agent, with credentials copied into each config file. Bifrost, the open-source MCP and LLM gateway written in Go and built by Maxim AI, is the best choice for enterprises running mission-critical AI workloads that require best-in-class performance, scalability, and reliability. This guide ranks the best MCP gateways for engineers and developers on setup effort, coding-agent integration, tool-level access control, and token efficiency, with configuration examples for the clients developers use daily.

What Is an MCP Gateway?

An MCP gateway is a control layer between AI clients and MCP servers that exposes many tool servers through one endpoint. For developers, it replaces per-client MCP configuration with a single connection, centralizes credentials, filters which tools each agent sees, and logs every tool call for debugging.

The Model Context Protocol, which Anthropic introduced in November 2024, standardizes how clients discover and call tools. It says nothing about how a developer should manage 15 MCP servers across four clients and two laptops. A gateway handles that layer. Our guide to MCP gateways for production AI agents covers the architecture in depth.

Developers usually adopt a gateway for four reasons:

• One configuration: Register MCP servers once and point every client at the gateway endpoint.
• Credential hygiene: API keys and OAuth tokens live in the gateway instead of in .mcp.json files checked into repositories.
• Smaller context windows: Tool filtering keeps a coding agent from loading hundreds of irrelevant tool definitions on each turn.
• Debuggability: A central log shows which tool the agent called, with which arguments, and what came back.

The differences between a gateway, a pass-through proxy, and a single server are laid out in MCP gateway vs MCP proxy vs MCP server. For the full reference design, see the Bifrost MCP gateway resource page.

What Developers Should Look for in an MCP Gateway

The best MCP gateways for developers are judged on how quickly they run locally, how cleanly they connect to coding agents, whether they filter tools per client, which transports they support, and whether they can move from a laptop to shared team infrastructure without a rewrite.

Transport support deserves a close look. The MCP transports specification defines STDIO and Streamable HTTP as the standard mechanisms, and a gateway that cannot spawn STDIO servers forces developers to wrap local tools in HTTP themselves. Bifrost connects to upstream servers over STDIO, HTTP, and SSE.

Best MCP Gateways Compared at a Glance

The best MCP gateways for developers split into three groups. Bifrost and agentgateway govern both model and tool traffic. Docker MCP Gateway and MCPJungle focus on aggregating MCP servers for local and team use, and Composio is a managed platform built around a library of hosted integrations.

1. Bifrost

The Bifrost AI gateway is an open-source MCP gateway and LLM gateway that runs as one Go service. Bifrost connects to upstream MCP servers as a client, exposes every connected tool through a single /mcp endpoint, and routes model requests from the same coding agents through an OpenAI-compatible API, so one gateway covers both halves of an agent's traffic.

Best for: Bifrost is built for enterprises running mission-critical AI workloads that require best-in-class performance, scalability, and reliability. It serves as a centralized AI gateway to route, govern, and secure all AI traffic across models and environments with ultra low latency. Bifrost unifies LLM gateway, MCP gateway, and Agents gateway capabilities into a single platform. Designed for regulated industries and strict enterprise requirements, it supports air-gapped deployments, VPC isolation, and on-prem infrastructure. It provides full control over data, access, and execution, along with robust security, policy enforcement, and governance capabilities.

Developer workflow

Bifrost starts with npx -y @maximhq/bifrost or docker run -p 8080:8080 maximhq/bifrost, and it includes a web UI for adding MCP servers and providers. In gateway mode, external clients such as Claude Code, Cursor, and Claude Desktop connect to http://localhost:8080/mcp and receive the aggregated tool set.

The Bifrost CLI goes a step further for terminal agents:

• One launcher: Running npx -y @maximhq/bifrost-cli configures base URLs, keys, and models for Claude Code, Codex CLI, Gemini CLI, and Opencode.
• Automatic MCP attachment: The CLI attaches the Bifrost MCP server to Claude Code, so tools are available without editing config files.
• Secure key storage: Virtual keys are stored in the operating system keyring, never in plaintext on disk.
• Tabbed sessions: Agents run in a persistent tabbed terminal UI with per-tab activity badges.

Tool filtering and authentication

Tool access in Bifrost is deny-by-default. A virtual key with no MCP configuration exposes no tools, except from clients an administrator marks as allowed by default. Tool filtering stacks across three levels (client configuration, request headers, and virtual key), and a tool must pass all of them.

Virtual MCPs bundle selected tools from several servers behind a stable /mcp/<slug> URL, which lets a team hand a frontend agent a different tool set than a database agent. Clients authenticate to /mcp with virtual key headers or through OAuth 2.1 browser consent, and Bifrost supports six upstream auth types, including per-user OAuth for services like GitHub and Notion.

Code Mode for large tool catalogs

Code Mode exposes four meta-tools instead of the full catalog, and the model writes Python (Starlark) that calls tools inside a sandbox. Tool definitions load on demand, and intermediate results stay in the sandbox rather than passing back through the model.

In Bifrost's three-round benchmark, Code Mode cut input tokens by 58.2% at 96 tools, 84.5% at 251 tools, and 92.8% at 508 tools across 16 servers, with a 100% pass rate in the largest round. The MCP gateway cost benchmark details the methodology, and how Bifrost cuts token costs in Claude Code and Codex CLI applies it to coding agents.

Performance and model routing

Bifrost adds 11 microseconds of overhead per request at 5,000 RPS with a 100% success rate in sustained benchmarks. The same gateway routes to 25+ providers and 10,000+ models, so a developer can run Claude Code against a non-Anthropic model, or Codex CLI against Claude, through one endpoint. Built-in observability records LLM and MCP log entries side by side, which makes it possible to trace an agent session from prompt to tool call.

2. Docker MCP Gateway

Docker MCP Gateway is the MIT-licensed engine behind the docker mcp CLI plugin and the MCP Toolkit in Docker Desktop. It runs each local MCP server in its own container and lets clients such as VS Code, Cursor, and Claude Desktop share one gateway configuration.

Best for: Developers already working in Docker Desktop who want container-isolated MCP servers on their own machine.

Key capabilities, as described in the project README:

• Container isolation: Each MCP server runs as a Docker container, and npx or uvx servers receive minimal host privileges.
• Profiles: Servers are grouped into profiles that connect to a client with docker mcp client connect, and profiles can be pushed to and pulled from OCI registries.
• Catalogs: Servers come from the Docker MCP Catalog, OCI images, the community MCP registry, or local files.
• Tool allowlists: Individual tools can be enabled or disabled per profile with dot notation such as github.create_issue.
• Secrets and OAuth: Credentials are managed through Docker Desktop secrets, with built-in OAuth flows.

Considerations: The prerequisites list Docker Desktop 4.59 or later with the MCP Toolkit enabled, although the CLI can run independently with a feature flag. The gateway runs over STDIO by default and serves multiple clients over SSE or streaming transports. The README does not describe per-user access control, model routing, or performance benchmarks. Developers who outgrow a single machine can compare this with connecting Claude Code to multiple MCP servers through one gateway.

3. Composio

Composio is a proprietary agent integration platform that provides a managed MCP gateway in front of its own library of hosted tool integrations. Composio's published materials describe more than 1,000 managed integrations with OAuth flows and schema updates maintained by Composio, available through managed cloud, private VPC, or an embedded SDK.

Best for: Product teams that want pre-built SaaS integrations such as Slack, GitHub, Jira, and Salesforce without running their own MCP servers.

Key capabilities, as described on Composio's MCP gateway comparison page:

• Per-team endpoints: Each team receives its own MCP URL that developers paste into Claude, Cursor, or ChatGPT, with SSO authentication.
• Action-level blocking: Toolkits can be allowlisted or blocklisted per team, and destructive actions can be blocked inside permitted toolkits.
• Identity: SSO through SAML or OIDC, with SCIM 2.0 provisioning mapping directory groups to teams.
• Audit trail: Tool calls are logged with user, team, tool, action, and outcome, with configurable retention and CSV export.
• Compliance: SOC 2 Type II and ISO 27001.

Considerations: Composio is proprietary, so teams with an open-source requirement cannot inspect or fork the gateway. Its value centers on the managed integration library, which means teams that already run their own MCP servers adopt more platform than they need. Composio's page does not publish LLM routing or a gateway latency figure. Teams that need self-hosted control with enterprise identity can compare the Bifrost Enterprise deployment options, including in-VPC installs.

4. agentgateway

agentgateway is an Apache 2.0 licensed proxy written in Rust and hosted as a Linux Foundation project. It covers LLM, MCP, and agent-to-agent (A2A) traffic, and it runs from a flat YAML configuration file or through a Kubernetes controller that supports Gateway API resources.

Best for: Platform engineers who want MCP and A2A traffic managed as Kubernetes Gateway API resources.

Key capabilities, as described in the project README:

• MCP gateway: Tool federation over STDIO, HTTP, SSE, and Streamable HTTP, with OpenAPI integration and OAuth authentication.
• LLM gateway: An OpenAI-compatible API for major providers with budget controls, load balancing, and failover.
• Security: JWT, API key, and OAuth authentication, RBAC through a CEL policy engine, rate limiting, and TLS.
• Guardrails: Regex filters, OpenAI moderation, AWS Bedrock Guardrails, Google Model Armor, and custom webhooks.
• Observability: OpenTelemetry metrics, logs, and tracing, plus a built-in UI.

Considerations: The project describes itself as in active development. The README does not document client-specific setup for Claude Code, Cursor, or Codex CLI, and it does not publish gateway overhead benchmarks. Teams deploying on Kubernetes can compare the equivalent Bifrost Kubernetes deployment guide.

5. MCPJungle

MCPJungle is a self-hosted MCP gateway released under the Mozilla Public License 2.0 and written in Go. It registers MCP servers once through a CLI and exposes them to Claude, Cursor, Copilot, and custom agents through a single Streamable HTTP endpoint, running either locally or as shared team infrastructure.

Best for: Individual developers and small teams that want a lightweight registry for MCP servers with a simple path to a shared deployment.

Key capabilities, as described in the project README:

• Quick start: docker compose up -d starts the server at http://localhost:8080/mcp, and servers register with mcpjungle register.
• Transports: Upstream servers can be Streamable HTTP or STDIO, with a dedicated stdio Docker image for npx and uvx servers.
• Tool groups: Curated subsets of tools are served from group-specific endpoints, and individual tools can be enabled or disabled.
• Storage: SQLite by default, with PostgreSQL for shared deployments.
• Enterprise mode: Access control that explicitly allows each MCP client to reach specific servers, plus OpenTelemetry observability.

Considerations: In development mode, every MCP client has full access to every registered server. In enterprise mode, access is granted per client at the server level, and only administrators can create tool groups. The README describes bearer-token upstream authentication and no LLM routing. Teams whose tool catalogs keep growing can compare tool groups with how Code Mode works in Bifrost.

Connecting Claude Code, Cursor, and Codex to an MCP Gateway

Claude Code, Cursor, and Codex CLI each connect to an MCP gateway differently. Claude Code adds the gateway as a remote HTTP MCP server, Cursor combines a custom model endpoint with MCP configuration, and Codex CLI routes through an OpenAI-compatible provider entry, so a gateway with documented setup for each client saves real integration time.

Claude Code MCP setup

Claude Code registers remote servers with claude mcp add --transport http, as described in the Claude Code MCP documentation. Pointing it at Bifrost takes one command:

claude mcp add --transport http bifrost http://localhost:8080/mcp \
  --header "Authorization: Bearer your-virtual-key" \
  --scope user

The --scope user flag makes the gateway available across all projects, while --scope project writes a shared .mcp.json for the repository. The full walkthrough, including identity modes for per-user MCP servers, is in the Bifrost Claude Code integration guide and our practical guide to using an MCP gateway with Claude Code.

Cursor MCP setup

Cursor accepts a Bifrost virtual key in its OpenAI API key field with the base URL overridden to the gateway, which gives Cursor access to any configured provider model. The Cursor setup guide covers model assignment for Chat, Agent, Inline Edit, and Tab Completion. Cursor requires a publicly reachable Bifrost URL for model traffic, so teams typically use a deployed gateway rather than localhost.

Codex MCP setup

Codex CLI connects through a named model_providers entry in config.toml that points base_url at the gateway's OpenAI-compatible path. The Codex CLI integration guide recommends the named provider over openai_base_url to avoid tool namespace conflicts with some providers. MCP tools configured in Bifrost are then available to Codex sessions routed through the gateway.

Which MCP Gateway Fits Your Workflow?

The best MCP gateway for a team depends on where its agents run and who manages the tools. A single developer on Docker Desktop has different needs than a platform team serving 200 engineers, and a team buying integrations has different needs than one building its own MCP servers.

Local-only tools often force a migration once a second engineer needs the same tools under different permissions, which per-key allow-lists avoid. The LLM gateway buyer's guide lists the questions to ask before committing, and our overview of how an MCP gateway centralizes agent tool access explains the underlying model. For the Bifrost reference architecture, see the MCP gateway resource hub.

Frequently Asked Questions

What is an MCP gateway?

An MCP gateway is a control layer that sits between AI clients and MCP servers. It aggregates many servers behind one endpoint, authenticates clients, filters which tools each client can call, and logs tool activity. Developers use it to replace per-client MCP configuration in Claude Code, Cursor, and Codex CLI with a single connection managed in one place.

Do I need an MCP gateway for local development?

A single developer with two or three MCP servers can manage without one. A gateway becomes useful once the same servers are configured across several clients, credentials start appearing in config files, or tool definitions begin crowding the context window. Starting with a gateway locally also means the setup carries over unchanged when a team adopts the same tools.

How do I connect Claude Code to an MCP gateway?

Claude Code connects to an MCP gateway with claude mcp add --transport http, followed by a name, the gateway URL, and an authorization header. For Bifrost, the URL is the gateway's /mcp endpoint and the header carries a virtual key. The --scope user flag makes the gateway available across projects, and the Bifrost CLI launcher for coding agents can attach it automatically.

Does an MCP gateway reduce token usage?

An MCP gateway reduces token usage by limiting the tool definitions that reach the model. Per-key tool filtering removes irrelevant tools, and Bifrost goes further with on-demand tool loading through Code Mode. In Bifrost benchmarks with 508 tools across 16 MCP servers, Code Mode reduced input tokens by 92.8% and estimated cost by 92.2%.

What are some alternatives to Docker MCP Gateway?

The best MCP gateways to consider as alternatives to Docker MCP Gateway are Bifrost, Composio, agentgateway, and MCPJungle. Docker's gateway centers on container-isolated servers on one machine. Bifrost adds per-key tool governance, OAuth client authentication, and model routing for shared use, Composio provides hosted integrations, agentgateway targets Kubernetes, and MCPJungle offers a lightweight self-hosted registry.

Is Composio open source?

No. Composio describes its MCP gateway as proprietary, available as managed cloud, private VPC, or an embedded SDK. Developers who need an open-source gateway they can self-host and inspect can choose Bifrost (Apache 2.0), agentgateway (Apache 2.0), Docker MCP Gateway (MIT), or MCPJungle (MPL 2.0).

Try Bifrost for Your Coding Agents

The best MCP gateways for developers remove per-client configuration without adding a new operational burden. Bifrost gives engineers one open-source gateway for MCP tools and model traffic, deny-by-default tool filtering per virtual key, one-command Claude Code setup, and Code Mode for large tool catalogs, with 11 microseconds of overhead at 5,000 RPS. Browse implementation patterns in the Bifrost resources library.

To see how Bifrost governs MCP tool access for engineering teams at scale, book a demo with the Bifrost team.