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Tunnel Client
openai/tunnel-client
Customer-run client for Secure MCP Tunnel: connect private or localhost MCP servers to ChatGPT, Codex, the Responses API, and AgentKit without exposing them to the public internet.
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README
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.
This CLI and its Go SDK run beside your private MCP server.
Applications call the OpenAI-hosted /v1/mcp/{tunnel_id} endpoint through their
MCP transport; the runtime receives those requests and delivers responses.
The poll/response endpoints are the runtime's queue protocol for client
implementers. See the architecture for the request flow
and the protocol when building a compatible runtime.
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/uibefore 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
- Selecting a regional control-plane endpoint? Use
--control-plane.residency,CONTROL_PLANE_RESIDENCY, or YAMLcontrol_plane.residency. See the endpoint catalog and mTLS settings. Endpoint selection is independent of regional Tunnel service availability. - 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.mdand usedocs/openapi.json. Optional client features use the commonX-Tunnel-Client-Capabilitiesheader. - 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-contextto carry W3C trace context in MCPparams._metaover stdio and Streamable HTTP. Opt-in local span export uses--tracing.enabled --tracing.file=/private/new-trace.jsonl. Complete traces require compatible service queue handoff and caller parent propagation first. - Forwarding the original HTTP request ID? MCP HTTP forwarding is enabled
by default. Use
--forward-request-id=mcp,harpoonto include Harpoon REST requests,--forward-request-id=mcp,oauthto include eligible queued OAuth discovery requests, or--forward-request-id=noneto disable automatic forwarding. The same setting is available asFORWARD_REQUEST_IDor top-level YAMLforward_request_id; see request ID forwarding. - 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, including DNS diagnostic logs for Android / Termux. - 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. It also installs Bash, Zsh, and Fish completions for that version.
If your shell does not load them automatically, follow
Homebrew's shell completion setup.
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
Start at macOS login
The Homebrew Formula supports brew services. It supervises
tunnel-client run using the profile at
$(brew --prefix)/etc/tunnel-client.yaml, starts at login, and restarts the
runtime after it exits. Installation and upgrades do not create or replace
that profile.
First, select the profile you already configured. If it belongs to a managed
alias, find its profile_path with tunnel-client runtimes status <alias> --json,
then run tunnel-client runtimes stop <alias> before starting the service.
Copy the profile to the service location, preserving your custom settings:
service_profile="$(brew --prefix)/etc/tunnel-client.yaml"
if [ -e "$service_profile" ]; then
cp -p "$service_profile" "$service_profile.backup.$(date +%Y%m%d%H%M%S)"
fi
install -m 600 /absolute/path/to/existing-profile.yaml "$service_profile"
Use absolute paths in this profile, including paths to MCP executables,
working directories, and secret files. The service includes Homebrew's bin
and sbin on PATH, but does not load your interactive shell configuration.
Replace shell-only env: references with persistent references such as this
existing profile field:
control_plane:
api_key: file:/Users/YOU/.config/tunnel-client/runtime.key
Store the runtime API key in that file with permissions 0600; keep its
directory private too. The service definition contains the profile path,
not the key. Validate the profile, then start the service as your logged-in
user, without sudo:
tunnel-client doctor --profile-file "$(brew --prefix)/etc/tunnel-client.yaml"
brew services start openai/tools/tunnel-client
brew services info openai/tools/tunnel-client
tunnel-client health --url http://127.0.0.1:8080 --json
The health command above uses the default listener. If your profile configures
a different health address or a health.url_file, use that address or
health --url-file /absolute/path/to/health-url instead. An active service
alone does not mean the tunnel is ready. Inspect
$(brew --prefix)/var/log/tunnel-client.log and any log.file destination in
your profile if startup fails.
Use Homebrew to manage this runtime:
# Reload the profile/key or pick up the installed version after a brew upgrade.
brew services restart openai/tools/tunnel-client
# Stop the runtime and disable automatic login startup.
brew services stop openai/tools/tunnel-client
The service uses Homebrew's stable opt path across upgrades. The CLI's
runtimes status and runtimes stop commands manage its own detached
processes; they do not discover or control the Homebrew service. Do not run
runtimes connect for the same tunnel while the service is active: that
command writes a generated profile and starts a separate runtime. Stop the
service before switching back to CLI management. Keep only one runtime active
for the tunnel during the switch, especially for stdio or stateful MCP servers.
The per-user macOS service runs during your login session, not before login
or after logout. Sleep suspends the Mac's work; wake allows the runtime's
network retries to resume. Homebrew's launchd service restarts an exited
process, but does not restart one merely because readiness fails. Start a
local HTTP MCP server through its own supervisor. For a server that starts
later, set mcp.startup_wait_timeout (for example, 2m) in the profile to
allow startup connection retries. If that window expires, restart the service
after the MCP server is available; the process can remain alive with its
startup probe failed. After a server restart, check readiness and logs;
existing MCP sessions may need to be initialized again. For a stdio target,
the runtime owns the MCP child. Do not assume interrupted tool calls are
replayed. See Supervising startup for
interpreting process liveness, OAuth discovery, readiness, and polling state.
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 ...for a foreground daemon attached to the current terminal or supervised by the OS; see macOS login startup. - For a long-lived local runtime managed by Codex, prefer
tunnel-client runtimes connect .... Do not usenohupordisownas the tunnel-client supervision path. - After
runtimes connect, checktunnel-client runtimes status <alias>before reporting success. Only report success when status shows the managed runtime running with health reported. Use--jsonwhen Codex needs the explicitprocess_running,healthy, andreadyfields.
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 viatunnel-client admin tunnels create|list|get ...withOPENAI_ADMIN_KEY.CONTROL_PLANE_API_KEY: create it in Runtime API keys; this is the key used bytunnel-client doctorandtunnel-client run.- For AWS workload identity, set
CONTROL_PLANE_AWS_IDENTITY_PROVIDER_IDandCONTROL_PLANE_AWS_SERVICE_ACCOUNT_ID. OPENAI_ADMIN_KEY: only fortunnel-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_KEYneed 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.
By default, tunnel-client restarts a supervised stdio child after an
unexpected exit, stdout EOF, or stdin write failure. Calls in progress may
fail, and legacy callers must initialize the replacement child before retrying.
If your deployment uses an external process supervisor to restart the whole
client, set --mcp.stdio-failure-policy=exit,
MCP_STDIO_FAILURE_POLICY=exit, or YAML mcp.stdio_failure_policy: exit.
That setting restores nonzero client exit on these failures; intentional
shutdown still exits successfully. Remove the new flag or YAML key before
downgrading to a version that does not recognize it.
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 the supported download, update tunnel-service's hard-coded public artifact URL alongside the release handoff.
Validate a source checkout with native Go tooling:
go build ./...
go test ./...
Independent tests, subtests, and fuzz seed cases use t.Parallel(). Give each
case its own mutable fixtures, and use t.Cleanup for resources shared by
parallel children. Keep dependent state transitions in one test. Keep tests
that mutate process-wide globals, environment variables, signals, or stdio
serial.
Check concurrent execution with the race detector and shuffled test order:
go test -race -shuffle=on -count=3 ./...
The E2E and mock-server packages default to two concurrent tests to bound
resource use. An explicit -parallel=N overrides that default.
SBOMs
The public repository includes deterministic six-platform dependency baselines for the full client, runtime, and runtime with Cloudflared. They inventory synthetic payloads built from declared offline source and vendor snapshots, including pinned Cloudflared module versions, purls, and CPEs. Do not hand-edit them; maintainers refresh them through the hermetic SBOM generation check when dependency inputs or a Cloudflared pin changes. The baselines are useful for dependency review and drift detection, but they do not claim that a public release ZIP contains the same bytes.
From a checkout of this public repository, verify that the mirrored baseline files match their mirrored manifest before importing them into a dependency scanner:
./scripts/verify_sbom_baselines.sh
That command proves the checkout's three baseline documents match
compliance/sbom-baseline-manifest.json and parse as SPDX 2.3. It does not
prove that any release archive contains those bytes.
Validate a downloaded release
Releases produced by the current release workflow publish a matching SPDX 2.3
sidecar for each ZIP, embed the same sidecar in the ZIP, cover both files in
SHA256SUMS.txt, and publish the workflow's signed Sigstore provenance bundle.
They also publish:
tunnel-client-vX.Y.Z-vulnerability-report.json, generated by a checksum-pinned Grype binary from exactly 18 release-specific SPDX sidecars: three flavors across six platforms, each bound to its matching ZIP and license-report SHA256, with the exact vulnerability-database SHA256 recorded;tunnel-client-vX.Y.Z.openvex.jsononly when the scan has findings, with every automated statement set tounder_investigationrather than claiming that a finding is fixed, exploitable, or not affected; andtunnel-client-vX.Y.Z-enterprise-evidence.json, which inventories the release evidence bytes, scanner/database identity, scan scope, and provenance boundary.
The vulnerability report explicitly records OCI images as not_scanned:
the release contract has multi-architecture OCI index digests, not exact
per-platform OCI manifest scan inputs. Every pre-bundle release artifact is
covered by SHA256SUMS.txt, PUBLIC_URLS.txt, and the signed provenance
bundle. The bundle is intentionally excluded from its own checksum and
signature subject set.
Older releases without .spdx.json sidecars cannot be archive/SBOM-validated
this way; releases without a *-provenance.sigstore.json bundle cannot be
provenance-validated this way. Use the release sidecar, not a checked-in
baseline, to validate downloaded bytes.
From a checkout of this public repository at the matching release tag, replace
the example tag and choose one of client, runtime, or
runtime-cloudflared. The commands require Bash, Python 3, curl, and the
GitHub CLI:
release=vX.Y.Z
platform=linux-amd64
flavor=runtime
prefix=tunnel-client-runtime
stem="${prefix}-${release}-${platform}"
base="https://github.com/openai/tunnel-client/releases/download/${release}"
bundle="tunnel-client-${release}-provenance.sigstore.json"
source_digest="$(git rev-parse HEAD)"
curl -fLO "${base}/${stem}.zip"
curl -fLO "${base}/${stem}.spdx.json"
curl -fLO "${base}/${stem}-licenses.txt"
curl -fLO "${base}/SHA256SUMS.txt"
curl -fLO "${base}/${bundle}"
gh attestation verify "${stem}.zip" \
--bundle "${bundle}" \
--repo openai/tunnel-client \
--signer-workflow openai/tunnel-client/.github/workflows/release.yml \
--source-ref "refs/tags/${release}" \
--source-digest "${source_digest}" \
--signer-digest "${source_digest}" \
--predicate-type https://slsa.dev/provenance/v1 \
--deny-self-hosted-runners
gh attestation verify "${stem}.spdx.json" \
--bundle "${bundle}" \
--repo openai/tunnel-client \
--signer-workflow openai/tunnel-client/.github/workflows/release.yml \
--source-ref "refs/tags/${release}" \
--source-digest "${source_digest}" \
--signer-digest "${source_digest}" \
--predicate-type https://slsa.dev/provenance/v1 \
--deny-self-hosted-runners
gh attestation verify "${stem}-licenses.txt" \
--bundle "${bundle}" \
--repo openai/tunnel-client \
--signer-workflow openai/tunnel-client/.github/workflows/release.yml \
--source-ref "refs/tags/${release}" \
--source-digest "${source_digest}" \
--signer-digest "${source_digest}" \
--predicate-type https://slsa.dev/provenance/v1 \
--deny-self-hosted-runners
gh attestation verify SHA256SUMS.txt \
--bundle "${bundle}" \
--repo openai/tunnel-client \
--signer-workflow openai/tunnel-client/.github/workflows/release.yml \
--source-ref "refs/tags/${release}" \
--source-digest "${source_digest}" \
--signer-digest "${source_digest}" \
--predicate-type https://slsa.dev/provenance/v1 \
--deny-self-hosted-runners
./scripts/verify_release_archive.sh \
--flavor "${flavor}" \
--archive "${stem}.zip" \
--sbom "${stem}.spdx.json" \
--checksums SHA256SUMS.txt
To verify the complete release evidence set, download every asset into a clean directory and run both fail-closed contract verifiers:
mkdir release-evidence
gh release download "${release}" \
--repo openai/tunnel-client \
--dir release-evidence
./scripts/verify_release_provenance.sh \
--bundle "release-evidence/${bundle}" \
--artifact-dir release-evidence \
--release "${release}" \
--source-digest "${source_digest}"
./scripts/verify_release_evidence.sh \
--artifact-dir release-evidence \
--release "${release}" \
--source-digest "${source_digest}"
Use prefix=tunnel-client with flavor=client, or
prefix=tunnel-client-runtime-cloudflared with
flavor=runtime-cloudflared. The bundle is the release workflow's signed
Sigstore evidence and supports verification without GitHub attestation lookup.
It is emitted after SHA256SUMS.txt is attested, so it is intentionally not
listed in that checksum file; gh attestation verify checks the bundle's
signature, transparency-log material, signer workflow, source ref, source
digest, and subject digest. The archive verifier then fails closed when the
published checksums do not match, the ZIP is too large or has unsafe,
duplicate, or non-regular members, its embedded sidecar differs from the
downloaded sidecar, or the SPDX SHA256 inventory does not match the extracted
payload. After it passes, import the matching .spdx.json file into the
dependency scanner of your choice. Runtime releases also publish a matching
*-scan-manifest.json that binds scanner scope, source archives, license
evidence, and the release sidecars.
For a fully disconnected verification environment, capture a trusted root from an independently trusted online environment before disconnecting:
gh attestation trusted-root > trusted_root.jsonl
Transfer that file with the release evidence and add
--custom-trusted-root trusted_root.jsonl to each gh attestation verify
command above. The release bundle removes the GitHub attestation API
dependency; the trusted-root file removes the remaining online trust-root
lookup.
Build the CLI binary from a source checkout. The Make target stamps the
checkout Git SHA into the version sent in User-Agent and
X-Tunnel-Client-Version:
make admin-ui
make tunnel-client
./bin/tunnel-client help quickstart
If you invoke Go directly, stamp the same metadata explicitly:
module_path="$(go list -m -f '{{.Path}}')"
git_sha="$(git rev-parse HEAD)"
mkdir -p bin
go build \
-ldflags "-X ${module_path}/pkg/version.GitSHA=${git_sha}" \
-o bin/tunnel-client \
./cmd/client
Narrow runtime artifacts
tunnel-client-runtime and tunnel-client-runtime-cloudflared are the
runtime-only customer surfaces. They intentionally expose only run plus
flag-based --help and --version; use the full tunnel-client binary for
onboarding, admin, Codex, and profile-management commands. The Cloudflare
flavor adds only the approved cloudflared.* settings and supervises a pinned
cloudflared companion.
Build either binary from a source checkout with its Make target (the shorter aliases are equivalent):
make tunnel-client-runtime # alias: make runtime
make tunnel-client-runtime-cloudflared # alias: make runtime-cloudflared
The targets write platform-specific binaries under bin/<goos>_<goarch>/ and
stable paths at bin/tunnel-client-runtime and
bin/tunnel-client-runtime-cloudflared (.exe on Windows). Inspect the exact
runtime flags with ./bin/tunnel-client-runtime run --help or
./bin/tunnel-client-runtime-cloudflared run --help.
Run the narrow runtime against an HTTP MCP server:
export CONTROL_PLANE_API_KEY='...'
export CONTROL_PLANE_TUNNEL_ID='tunnel_0123456789abcdef0123456789abcdef'
export MCP_SERVER_URL='https://mcp.example.com/mcp'
./bin/tunnel-client-runtime run
For managed Cloudflare provisioning, use the Cloudflare flavor. Release
archives place the pinned cloudflared executable beside the runtime; for a
source-only build, point to an existing companion explicitly:
./bin/tunnel-client-runtime-cloudflared run \
--cloudflared.managed \
--cloudflared.path /path/to/cloudflared
To build the corresponding Linux images, use make build-image-runtime and
make build-image-runtime-cloudflared; the Cloudflare image includes its pinned
companion and both images use run as their entrypoint.
Contributors can run the compatibility suite with make test-runtime. Its
host-binary checks compare the full client and runtime flavors with the same
profile bytes, environment, flags, local control-plane/MCP/OAuth/proxy/TLS
fixtures, and shutdown signal. The same target also packages native
release-shaped ZIPs and checks that they verify, extract, identify the expected
flavor, and expose run --help; that ZIP smoke is not a second fake-service
parity run.
After building the runtime images, make runtime-container-compatibility
runs a deployment smoke for their default and overridden entrypoints with
read-only profile/Secret mounts and hardened container settings. It uses
intentionally unreachable local endpoints to check startup surfaces and
SIGTERM, not to compare image behavior with the full client or assert
/readyz readiness. An optional local Kubernetes deployment smoke is
available with TUNNEL_CLIENT_RUNTIME_K8S_COMPAT=1 make runtime-k8s-compatibility; it requires Docker plus kind or k3d, checks
the runtime Pods' mounted profile/Secret and /healthz surface, and does not
contact external services.
Public releases use plain semantic-version tags such as v0.0.10. Source
archives from release tags carry the release version in
pkg/version/VERSION. A plain go build from a downloaded release .tar.gz
therefore reports the tag semantic version through tunnel-client --version,
User-Agent, and the explicit control-plane version headers. Source-checkout
builds made with the Make target or explicit linker flag above append the Git
SHA to that semantic version.
Supported release archives also bundle pinned cloudflared 2026.10.2 beside
the CLI for Linux amd64/arm64, macOS amd64/arm64, and Windows
amd64/arm64.
Official release images are published at ghcr.io/openai/tunnel-client for
Linux amd64 and arm64; they bundle the matching companion. Pin an exact
vX.Y.Z tag or digest for production. Stable releases also update the
X.Y and latest aliases; prereleases do not. For a logical tunnel created
with managed Cloudflare provisioning, let the authenticated client fetch the
runtime token and start the companion without distributing a static token:
tunnel-client run \
--cloudflared.managed \
--control-plane.tunnel-id tunnel_0123456789abcdef0123456789abcdef \
--mcp.server-url https://mcp.example.com/mcp
For a pre-provisioned Cloudflare tunnel, a static token remains available as an explicit override and is never put in argv:
export CLOUDFLARED_TOKEN='...'
tunnel-client run \
--cloudflared.token env:CLOUDFLARED_TOKEN \
--control-plane.tunnel-id tunnel_0123456789abcdef0123456789abcdef \
--mcp.server-url https://mcp.example.com/mcp
See docs/deployment/cloudflared.md for
platform coverage, readiness/failure behavior, Go module provenance, and
security-update ownership.
If an operator intentionally runs cloudflared without tunnel-client, print
a token-free production config and keep the token in a separate secret file:
tunnel-client cloudflared config \
--token-file /run/secrets/cloudflared/token \
> /etc/cloudflared/config.yml
TUNNEL_MANAGEMENT_DIAGNOSTICS=false \
cloudflared tunnel --config /etc/cloudflared/config.yml run
Fastest Codex terminal path:
tunnel-client codex assistant "Summarize what tunnel-client is doing in this checkout."
tunnel-client codex status
tunnel-client codex plugin install
tunnel-client runtimes list
tunnel-client help plugin
tunnel-client codex plugin uninstall
Choose the raw binary when you want the smallest possible setup surface.
Choose tunnel-client codex assistant when you want the fastest Codex-native
terminal path. Choose the plugin when you want a Codex-local entrypoint over
the native runtimes / admin-profiles command trees.
Starter prompts for Codex:
Figure out what tunnel-client is for from the binary help, then get me to /ui with the shortest local path.I only have the source checkout. Figure out how to build tunnel-client, then get me to /ui with the shortest local path.Use tunnel-client to create or reuse a profile, run doctor --explain, and then start the foreground daemon attached to this terminal.Run tunnel-client codex assistant and summarize what this checkout is for in one sentence.
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