tunnel-client

Secure MCP Tunnel client

tunnel-client is the customer-run agent behind Secure MCP Tunnel. It connects a private or localhost MCP (Model Context Protocol) server to ChatGPT, Codex, the Responses API, and AgentKit through an OpenAI-hosted MCP tunnel endpoint, while keeping the MCP server off the public internet.

Use it when:

• You have an MCP server on a laptop, VM, Kubernetes cluster, or private network and need an OpenAI-hosted product to reach it.
• Security will not approve a new inbound firewall rule or public endpoint for the MCP server.
• You want an operator-visible daemon with /healthz, /readyz, /metrics, and /ui before a connector or API call depends on it.

If you searched for "secure MCP tunnel", "MCP tunnel ChatGPT", "connect local MCP server to ChatGPT", "connect local MCP server to Codex", "localhost to ChatGPT", or "Codex local MCP", start with tunnel-client help quickstart, then read the onboarding guide below.

Start Here

• Need the shortest working path from localhost or a private MCP server to ChatGPT or Codex? Start with docs/onboarding.md.
• Need the customer-shareable network and trust-boundary story? Read docs/architecture.md.
• Need roles, groups, tunnel IDs, or API keys? Read docs/permissions.md.
• Need Docker, Kubernetes, or VM deployment guidance? Read docs/deployment/overview.md.
• Need to debug readiness, connector discovery, or OAuth? Read docs/troubleshooting.md.
• Building a compatible client in another language? Read docs/protocol.md and use docs/openapi.json. Optional client features use the common X-Tunnel-Client-Capabilities header.
• Upgrading for server-directed polling placement? Read the routing correction and activation notes. Supporting clients work with existing services immediately; corrections are enabled separately after client release. No configuration change is needed.
• Using MCP timing or distributed tracing? Read the timing release and rollback guidance. Trace forwarding is disabled by default; opt in with --mcp.forward-trace-context to carry W3C trace context in MCP params._meta over stdio and Streamable HTTP.
• Using a namespaced tunnel ID? Preserve the full ID returned by the service. The client accepts legacy IDs and aliases with a four-character namespace; see tunnel identifiers.
• Embedding an MCP server directly in a Go process? Use the Go SDK with the MCP SDK's in-memory transport; see examples/go-sdk-inmemory.

Try the embedded demo

With a runtime API key and tunnel ID, run the built-in server_info, echo, and uppercase tools without a separate MCP server:

export CONTROL_PLANE_API_KEY="sk-..."
export CONTROL_PLANE_TUNNEL_ID="tunnel_0123456789abcdef0123456789abcdef"
tunnel-client run --embedded-stateless-mcp-stub --health.listen-addr 127.0.0.1:0

--embedded-stateless-mcp-stub uses stateless MCP handling even when a client sends initialize and notifications/initialized. It issues no MCP session ID, and these demo tools do not require MCP session affinity between processes. OAuth and application state have separate requirements.

--embedded-mcp-stub keeps its existing compatibility behavior: legacy initialization and session requests use stateful handling; self-contained modern discovery and tool requests use stateless handling. Choose one embedded mode per run. Both share the embedded listen-address, Unix-socket, server-name, and server-version options; see embedded demo configuration for defaults and target conflicts.

Embed as a Go SDK

The module can run in the same process as a Go MCP server. The MCP server does not need to bind a port or use stdio: give the server side of an in-memory MCP transport pair to your server and the client side to tunnelclient.New.

go get github.com/openai/tunnel-client

import (
    "context"

    "github.com/modelcontextprotocol/go-sdk/mcp"
    tunnelclient "github.com/openai/tunnel-client"
)

ctx := context.Background()
server := mcp.NewServer(&mcp.Implementation{Name: "my-server", Version: "1.0.0"}, nil)
serverTransport, tunnelTransport := mcp.NewInMemoryTransports()
go server.Run(ctx, serverTransport)

client, err := tunnelclient.New(tunnelclient.Config{
    TunnelID: "tunnel_0123456789abcdef0123456789abcdef",
    APIKey:   apiKey,
}, tunnelTransport)
if err != nil {
    return err
}
return client.Run(ctx)

The runnable Go SDK example registers an echo tool and connects it to the OpenAI Tunnel control plane.

Documentation Map

• Public Secure MCP Tunnel guide: developers.openai.com/api/docs/guides/secure-mcp-tunnels
• Shareable end-user guide: docs/end-user-guide.md
• Start here: docs/onboarding.md
• Permissions, roles, and groups: docs/permissions.md
• Architecture diagrams: docs/architecture.md
• Connector behavior: docs/connectors.md
• Wire protocol for client implementers: docs/protocol.md
• OpenAPI contract: docs/openapi.json
• Enterprise customer handoff: docs/enterprise-customer-onboarding.md
• Configuration reference: docs/configuration.md
• Deployment guides: docs/deployment/overview.md
• Bundled Cloudflare companion: docs/deployment/cloudflared.md
• Troubleshooting: docs/troubleshooting.md
• Development & testing: docs/development.md
• In-memory Go SDK example: examples/go-sdk-inmemory
• Roadmap / design notes: docs/roadmap.md

Install with Homebrew

On macOS, Homebrew is the supported installation path. Directly downloaded release ZIPs are not currently notarized and can be blocked by Gatekeeper. If a manually downloaded archive is blocked, do not use xattr, spctl, or Open Anyway to bypass the check; install from the official OpenAI tap instead:

brew install openai/tools/tunnel-client

Verify the installed version, then start with the guided setup:

tunnel-client --version
tunnel-client help quickstart

The Formula installs the matching tunnel-client, bundled cloudflared, and companion manifest together, while exposing only the tunnel-client command. For Docker, Kubernetes, or VM deployments, see docs/deployment/overview.md.

To generate the shareable guide output locally:

make end-user-guide-screenshots
make end-user-guide-html
make end-user-guide-slides

For Codex / Copilot

If you want the shortest supported path from a local or localhost MCP server to ChatGPT or Codex, start with tunnel-client help quickstart. For Codex plugin lifecycle work, use the native tunnel-client runtimes ... and tunnel-client admin-profiles ... command trees surfaced by tunnel-client help plugin.

Supervision choice:

• Use tunnel-client run ... when you intentionally want a foreground daemon attached to the current terminal.
• For a long-lived local runtime managed by Codex, prefer tunnel-client runtimes connect .... Do not use nohup or disown as the tunnel-client supervision path.
• After runtimes connect, check tunnel-client runtimes status <alias> before reporting success. Only report success when status shows the managed runtime running with health reported. Use --json when Codex needs the explicit process_running, healthy, and ready fields.

Use these exact setup pages during first use:

• Tunnels management and supported tunnel-client download: https://platform.openai.com/settings/organization/tunnels
• Organization roles: https://platform.openai.com/settings/organization/people/roles
• Organization groups: https://platform.openai.com/settings/organization/people/groups
• Runtime API keys: https://platform.openai.com/settings/organization/api-keys
• Admin API keys: https://platform.openai.com/settings/organization/admin-keys
• ChatGPT connector settings: https://chatgpt.com/#settings/Connectors

Which value comes from where:

• CONTROL_PLANE_TUNNEL_ID: create or inspect it in Tunnels management, or via tunnel-client admin tunnels create|list|get ... with OPENAI_ADMIN_KEY.
• CONTROL_PLANE_API_KEY: create it in Runtime API keys; this is the key used by tunnel-client doctor and tunnel-client run.
• OPENAI_ADMIN_KEY: only for tunnel-client admin tunnels list|create|update|delete. Do not use the admin key for the long-lived daemon.

Required tunnel permissions:

• Runtime users and the principal that creates CONTROL_PLANE_API_KEY need Tunnels Read + Use.
• Tunnel managers need Tunnels Read + Manage, plus Use if they also run the daemon or attach ChatGPT connectors.
• Admin-key creators need the Platform admin-key permission in addition to any tunnel permissions they need.

See docs/permissions.md for the group/role workflow and screenshots.

Binary-first flow:

tunnel-client help quickstart
tunnel-client profiles samples list
tunnel-client profiles samples show sample_mcp_enterprise_proxy
tunnel-client init --sample sample_mcp_stdio_local --profile local-stdio --tunnel-id tunnel_0123456789abcdef0123456789abcdef --mcp-command "python /path/to/server.py"
tunnel-client doctor --profile local-stdio --explain
tunnel-client run --profile local-stdio
tunnel-client run --profile-file ./profiles/local-stdio.yaml

Stdio deployment limit: run only one active tunnel-client instance per tunnel ID when using --mcp.command / MCP_COMMAND. Multiple active instances sharing that tunnel ID are not supported, including overlap during a restart. Each instance launches a separate MCP child, and initialization and later requests can reach different children. Stop the old instance before starting its replacement, or use distinct tunnel IDs for independent instances. See stdio deployment limits.

Stdio initialization is checked automatically. Legacy calls require a successful initialize exchange followed by notifications/initialized; premature calls return mcp_initialization_required immediately. Self-contained MCP requests using protocol version 2026-07-28 or later pass through without a handshake. The caller owns initialization, including after child replacement. See configuration for lifecycle behavior.

If you need the tunnel id or runtime/admin keys first, open the matching URL above before running init. If your rollout has self-serve tunnel access, create the tunnel yourself in Tunnels management or with tunnel-client admin tunnels create, then export the returned id as CONTROL_PLANE_TUNNEL_ID and a separate runtime key as CONTROL_PLANE_API_KEY. Create or verify the connector from the ChatGPT settings URL above only while tunnel-client run ... is healthy, and keep the daemon running for connector discovery and every MCP call from ChatGPT.

The Platform Tunnels page download button is sourced from tunnel-service's gated tunnel metadata response. When a new public tunnel-client release becomes