MCP Gateway: How to Manage Multiple MCP Servers Behind One Endpoint

You start with one MCP server. Then two. Then five. Before long you're maintaining a dozen MCP servers across Claude Code, Cursor, a custom agent, and whatever client you adopt next — each with its own config file, its own copy of your API keys, and its own runtime processes. Add a server and you edit every client. Rotate a key and you edit every client.

An MCP gateway is the architectural answer to that sprawl. This guide covers what an MCP gateway actually is, how one works at the protocol level, how it differs from a proxy or a registry, when you should run one, and how MCP2Skill implements the pattern with workspaces, scoped endpoints, and call-level observability.

What is an MCP gateway?

An MCP gateway is a single MCP-compatible endpoint that sits between your AI clients and your MCP servers. Instead of each client connecting directly to every server, clients connect once to the gateway, and the gateway aggregates the upstream servers, filters which tools are exposed, routes each call to the server that owns it, and records what happened.

If you're new to the protocol itself, start with What is MCP (Model Context Protocol)? — this article assumes you already know what a tool call is.

A gateway typically takes on five jobs:

Why per-client MCP configuration breaks down

Direct client-to-server MCP is fine for one client and two servers. It degrades in five specific ways as you scale.

1. Configuration duplication grows as N x M

With N clients and M servers, you maintain N x M configurations. Three clients and eight servers is 24 config blocks that must stay in sync by hand. They don't stay in sync — you get drift, and drift shows up as a tool that silently exists in one client and not another.

2. Process duplication

stdio servers are launched as child processes by whatever connects to them. Three clients using the filesystem MCP means three filesystem MCP processes, three sets of file handles, three copies of that server's memory footprint. Multiply across a dozen servers and your laptop is running redundant infrastructure all day.

3. Secret sprawl

Every direct config is another place your GitHub token, database URL, or vendor API key sits in plaintext on disk. Rotating a credential means finding all of those copies. Revoking access from one client means editing that client's file — there's no central switch.

4. An unfiltered tool surface

Clients load the full tool list from every server they connect to. The GitHub MCP server alone exposes dozens of tools. Connect four or five servers and a large share of your context window is tool schemas the current task will never use — before the agent does anything. (We measured this problem in detail in How to Reduce MCP Token Waste with Skills.)

5. Zero observability

When a call fails, most clients tell you only that it failed. Was it the client, the transport, the server, an expired OAuth grant, or the tool's own error? Without a central record of requests and responses, you're guessing.

How an MCP gateway works

Architecturally, a gateway is an MCP server to your clients and an MCP client to your servers:

  Claude Code  ─┐                                  ┌─► filesystem MCP   (stdio, 1 process)
  Cursor       ─┼─►  MCP gateway endpoint  ────────┼─► GitHub MCP       (Streamable HTTP)
  Custom agent ─┘    one URL + one API key         └─► internal MCP     (SSE + OAuth)
                     one runtime, one log

A single request travels this path:

1. Connect and identify capabilities. The client opens the gateway URL and exchanges the protocol metadata and capabilities needed for that request. Gateways that support earlier MCP revisions also handle the legacy initialize handshake for compatible clients.
2. List tools. On tools/list, the gateway queries each upstream server it fronts, merges the results, drops anything you've filtered off, and returns one list.
3. Disambiguate names. Two servers can both expose a search tool. The MCP spec does not define namespacing for aggregation — the tool name is just expected to be unique — so collision handling is the gateway's responsibility, usually by prefixing tool names with the source service's identifier.
4. Route the call. On tools/call, the gateway maps the (namespaced) tool back to its owning server, attaches that server's credentials, and forwards the call.
5. Translate transports. Upstream stdio servers are local child processes; the gateway speaks Streamable HTTP to clients and stdio to those processes. That translation is what makes a local-only server reachable by a client that only speaks HTTP.
6. Record it. Request, response, duration, and error land in the gateway's log before the result goes back to the client.

Two protocol details worth knowing when you evaluate gateways:

• Streamable HTTP is the current recommended HTTP transport, introduced in the 2025-03-26 revision. The older HTTP+SSE transport has been deprecated since then and is scheduled for removal, so a gateway that only speaks legacy SSE to clients is a liability. Recent spec revisions have also moved toward a stateless, request-oriented model while retaining compatibility guidance for older clients.
• Authorization is optional in MCP and only applies to HTTP transports. When used, it's a subset of OAuth 2.1: servers advertise their authorization server via Protected Resource Metadata (RFC 9728), and clients must use PKCE. For stdio servers, credentials come from the environment instead — which is precisely why holding them in one gateway beats scattering them across client config files.

Gateway vs. proxy vs. aggregator vs. registry

These four terms get used interchangeably and shouldn't be.

A gateway is the runtime control point. A registry is a catalog. Most teams end up wanting both — discover a server from a registry, then run it behind the gateway.

Where the gateway runs: three deployment models

MCP2Skill is a desktop-first gateway: the runtime lives on your machine next to your local servers and your secrets, with an optional remote-access toggle when you deliberately want other machines to connect.

What to look for in an MCP gateway

A practical checklist when comparing options:

1. Transport coverage on both sides — stdio, SSE, and Streamable HTTP upstream; Streamable HTTP to clients.
2. Tool-level filtering, not just server-level enable/disable.
3. Multiple scoped endpoints, so different clients can see different tool sets from the same install.
4. Namespacing that survives two servers exposing the same tool name.
5. Credential custody, including OAuth flows for remote servers.
6. Access control on the gateway itself — at minimum an API key, and a clear stance on local-only vs. remote listening.
7. Call logs with request and response payloads, not just success counters.
8. Service logs for the upstream processes, so you can tell a crashed server from a rejected call.
9. Config import/export, so onboarding an existing setup isn't retyping it.
10. An answer for token cost — filtering helps, but ask what happens when the filtered list is still large.

Concrete use cases

One config across three clients. Configure eight MCP servers once. Paste the same gateway JSON into Claude Code, Cursor, and your own agent. Adding a ninth server is one edit, not three.

Per-project tool scoping. A frontend endpoint exposes the browser and filesystem tools; a data endpoint exposes the warehouse and BI tools. Same install, two tool surfaces, no duplicated server configs.

Least privilege for destructive tools. A server that exposes both read_file and delete_file doesn't have to expose both to every agent. Turn the destructive tool off on the endpoint your autonomous agent uses, keep it on the one you drive by hand.

Making a local server reachable. A stdio server on your desktop can't be used by a client that only speaks HTTP. Behind a gateway it becomes an HTTP endpoint — and with remote access enabled and an API key set, another machine on your network can use it too.

Diagnosing a flaky server. "The tool list looks right but calls fail" is unanswerable from the client side. From the gateway you check the call log for the failing request, then the service log for what that server printed when it died.

Trimming the tool surface before it reaches the context window. Every tool you filter off an endpoint is a schema that never enters the model's context. This is the gateway's honest contribution to token cost — see the comparison with Skills below.

How MCP2Skill implements the gateway pattern

MCP2Skill is a desktop app that runs your MCP servers once and exposes them through managed endpoints.

Services are the source of capability

Add servers as STDIO (command, args, env, working directory), SSE, or Streamable HTTP (URL plus custom headers), or import an existing config from a client you already use. Remote servers that require OAuth get an authorization flow with explicit status — authorization required, authorizing, authorized, expired — so an expired grant is visible instead of showing up as mysterious call failures.

Workspaces define the boundary

A workspace groups several MCP services and then filters, tool by tool, which of their tools stay enabled. Filtering is two-layered: a tool must be enabled both at the service level and at the workspace level before a client can see it. That's what lets the same service expose a wide surface in one workspace and a deliberately narrow one in another, without maintaining near-duplicate service configs.

Three endpoint scopes

Every workspace gets its own gateway endpoint, and you pick the scope that matches the job:

For stable, day-to-day use, a workspace endpoint you created yourself is the right default; ALL is a debugging tool. Full details in Tool Selection and Endpoints.

Copy the endpoint, or copy the JSON

From a service or workspace detail page you can copy either the raw endpoint URL — if you'd rather hand-write the client config — or a ready-made JSON block containing the service name, connection type, gateway URL, and required request headers. If you've enabled an API Key, the auth header is already in the JSON, which is the main reason to prefer it. See Connect External AI Clients for the client-side walkthrough.

Access control lives in one place

Settings control the gateway port, the remote-access toggle, and API Key authentication (enable, view, copy, regenerate). Enabling remote access is a deliberate decision: turn it on only when you actually need off-machine clients, and enable the API Key at the same time. Regenerating the key invalidates the config in already-connected clients, so re-copy the JSON afterward. See General and MCP Settings.

Observability comes free with the boundary

Because every call crosses the gateway, MCP2Skill can show:

• Dashboard — installed services, running services, available tools, calls today, success rate, average response time, recent calls, an activity heatmap, service load, and a client leaderboard that tells you which client is generating the traffic.
• Statistics — the same picture reviewed over a time range.
• Call logs — which call failed, when, from which service, workspace, and client, with the request and response.
• Service logs — what an upstream server actually printed during startup, connection, auth, or crash.

The practical loop: change a config, make one real call, then confirm it in the dashboard or logs. Logs and Diagnostics covers the troubleshooting path in full.

Gateway path vs. Skill path

A gateway solves configuration, reuse, and visibility. It does not change when tool definitions load — a client connected to a gateway still pulls the whole (filtered) tool list up front. Cutting that cost structurally is what the Skill path is for: a Skill exposes a short description first and loads full instructions only when a task matches. Anthropic's own code-execution demo reduced tool-definition overhead from 150,000 tokens to 2,000 — a 98.7% reduction — by letting the agent discover tools on demand.

MCP2Skill's default recommendation: if your agent supports Skills, take the Skill path for your most-used tools, and keep the gateway for everything else. Skills generated from a workspace still call that workspace's endpoint, so the tool filtering you configured applies either way — the two paths share one boundary. See MCP vs Skills for the decision framework and how to convert any MCP into a Skill for the conversion workflow.

Get started in five steps

1. Add your MCP servers to MCP2Skill once — manually, or by importing the config you already have in Claude Code or Cursor.
2. Create a workspace and filter it down to the tools that scenario actually needs.
3. Copy the workspace JSON into every client that needs standard MCP access.
4. Enable the API Key before you turn on remote access.
5. Make one real call and check the dashboard — if the call record appears, the client, gateway, and server chain are working end to end.

Then convert your highest-frequency workflows into Skills and measure the token difference. One config, one runtime per server, a tool surface you chose deliberately, and a log for everything your agents actually did.

FAQ

What is an MCP gateway?

An MCP gateway is a single MCP-compatible endpoint that sits between AI clients and MCP servers. It aggregates multiple servers into one tool list, filters which tools each endpoint exposes, holds the upstream credentials, routes each tools/call to the server that owns it, and records every call. Clients configure one connection instead of one per server.

Is an MCP gateway the same as an MCP proxy?

No. A proxy forwards traffic to a single upstream server, typically to bridge transports or add authentication. A gateway aggregates many servers and adds a policy layer on top — tool filtering, scoped endpoints, credential custody, and observability. An aggregator sits in between: it merges tool lists but usually stops short of per-client scoping and logging.

Does an MCP gateway reduce token usage?

Only indirectly. A gateway lets you decide which tool definitions exist on a given endpoint, so filtering a 60-tool surface down to 12 removes 48 schemas from the context window. But the surviving definitions still load up front. To change when definitions load, convert MCP tools into Skills, which expose a short description first and load full instructions only when a task matches — the mechanism behind the 98.7% reduction Anthropic measured.

Which AI clients can connect to an MCP gateway?

Any MCP-compatible client — Claude Code, Cursor, custom agents, and anything else that speaks the protocol. The gateway looks like an ordinary MCP server to them, so no client-side changes are needed beyond pointing the config at the gateway URL and including the auth header if a key is enabled.

What happens if two MCP servers expose a tool with the same name?

The MCP specification treats a tool's name as a unique identifier and doesn't define namespacing for aggregation, so resolving collisions is the gateway's job — typically by prefixing tool names with the source service's identifier. In MCP2Skill, a service's name identifier is used for the tool namespace and its endpoint, which is why it's worth choosing a stable one and not renaming it casually.