Using ACP agents

Agent Canvas can drive your conversations with the built-in OpenHands agent or with an external ACP agent — Claude Code, Codex, or Gemini CLI. This guide explains what ACP agents are, how to onboard one, and how to switch agents or models later.

What is an ACP agent?

The Agent Client Protocol (ACP) is a standard for talking to coding agents over JSON-RPC on stdio. Instead of Agent Canvas calling an LLM directly, the Agent Server spawns the agent's own CLI as a subprocess and relays each turn to it. The external agent manages its own LLM, tools, and execution; Agent Canvas sends messages and renders what comes back.

flowchart LR
    canvas["Agent Canvas
(this UI)"]
    server["Agent Server"]
    acp["ACP subprocess
(e.g. claude-agent-acp)"]
    llm["LLM provider
(Anthropic / OpenAI / Google)"]
    canvas -- "PATCH /api/settings
(agent_kind, acp_*)" --> server
    canvas -- "conversation turns" --> server
    server -- "spawn + JSON-RPC over stdio" --> acp
    acp -- "API calls" --> llm

The Agent Server owns the subprocess and the credentials; Agent Canvas only records which agent to run and surfaces a form for the secrets it needs. The agent choice is stored per backend, so switching backends can switch agents.

Supported providers

The provider list is sourced from the SDK registry (openhands.sdk.settings.acp_providers, mirrored into @openhands/typescript-client) and enriched with Canvas UI metadata in src/constants/acp-providers.ts. Adding or changing a provider happens upstream in the SDK, not here.

See Authentication for how each one authenticates.

Authentication

[!IMPORTANT] ACP agents authenticate two ways: a subscription login, or an API key — and the onboarding fields are optional. If you're already signed in to the provider's CLI on the machine the agent runs on, it reuses that login automatically, so locally you often don't need a key at all. The login takes priority over an API key: while you're signed in, a key set in the environment isn't used — so the onboarding key fields do nothing and can be left blank.

A "subscription login" is the credential the provider's own CLI stores when you sign in once — a file in your home directory, or, for Claude Code on macOS, the system Keychain. When the Agent Server runs on that same machine (a local or self-hosted backend), the provider CLI finds that login automatically — no API key required. On a clean cloud sandbox there's no stored login, so an API key is needed instead.

All three collect an optional API key (+ base URL) in onboarding. As noted above, a subscription / OAuth login takes priority over an API key — when the provider's CLI is signed in, a key set in the environment is not used. Verified per provider:

• Codex — codex login status keeps reporting the ChatGPT login even with OPENAI_API_KEY set.
• Gemini CLI — uses the OAuth auth type chosen at gemini login; GEMINI_API_KEY is only consulted if you switch the auth type. The free Google login is the common no-key path locally — sign in once and it just works.
• Claude Code — with both present, claude auth status reports it is authenticated via the subscription (claude.ai), not the key. The login is auto-detected from the macOS Keychain (or ~/.claude/.credentials.json on Linux); CLAUDE_CONFIG_DIR is not required for it — it only relocates Claude Code's config directory (settings/history, not the token; e.g. for containers or multiple accounts) and signals the SDK to strip a conflicting ANTHROPIC_API_KEY / ANTHROPIC_BASE_URL.

The one exception is the base URL (*_BASE_URL): a custom value points the CLI at a different endpoint (a proxy or gateway) and does take effect even under a login — for Gemini it rides the ACP gateway param. It's an advanced override, not needed for normal use.

Onboarding an ACP agent

First-time users get a four-step onboarding modal. To onboard an ACP agent:

1. Choose agent — pick Claude Code, Codex, or Gemini CLI instead of OpenHands. The choice is saved immediately to your backend's settings.

2. Check backend — confirms Agent Canvas can reach the Agent Server.

3. Set up credentials — enter the provider's credentials. Beyond the API key (+ optional base URL), this step also collects the credentials a containerized backend needs, since a fresh container has no host login:

   • Codex — CODEX_AUTH_JSON (the contents of ~/.codex/auth.json).
   • Claude Code — CLAUDE_CODE_OAUTH_TOKEN (a Pro/Max OAuth token).
   • Gemini CLI — GOOGLE_APPLICATION_CREDENTIALS_JSON (Vertex SA / ADC JSON) plus GOOGLE_CLOUD_PROJECT, GOOGLE_CLOUD_LOCATION, and GOOGLE_GENAI_USE_VERTEXAI.

   On a local backend the step is optional (a host login is reused automatically); on a Docker / cloud backend it's required, because there's no host login to fall back on. When the login probe detects an existing session, the step shows a "you're already signed in" banner and stays skippable.

4. Say hello — creates your first conversation and closes the modal.

[!NOTE] On a local backend every credential field is optional and the step is skippable. Leave a field blank to reuse a key already set on the backend, or to authenticate the agent through a subscription / OAuth login instead.

How credentials reach the agent

Each credential you enter is saved as a global secret whose name is exactly the environment variable the Agent Server exports into the ACP subprocess (e.g. ANTHROPIC_API_KEY). Saving in onboarding is identical to adding the secret under Settings → Secrets, where you can edit or remove it anytime. Keeping the secret name equal to the env var is what makes a saved key actually reach the provider CLI.

Running ACP agents in a Docker container

The walkthrough above assumes the Agent Server runs on your own machine, where the provider CLIs reuse a host login. You can also run the Agent Server in a container — Canvas drives it the same way, but since a fresh container has no host login, you supply credentials through the UI and Canvas sends them inline on the conversation start request.

A ready-to-run setup lives in examples/acp-docker/ (docker compose up, then point Canvas at it). In short:

# 1. Agent Server in a container (CORS allows localhost, so the browser talks
#    to it directly). The image pre-installs the ACP CLI wrappers. New
#    canvas_ui_control calls use client_tools; the Python mount keeps
#    pre-migration conversations loadable when persisted metadata imports
#    canvas_ui_tool.
# Minimum image: 1.28.0-python (first compatible ACP provider/model protocol
# surface for current Canvas). Override SHA with a newer build.
docker run -d --name oh-acp -p 8010:8000 -v acp-data:/workspace \
  -v "$(pwd)/tools:/canvas-tools:ro" -e OH_EXTRA_PYTHON_PATH=/canvas-tools \
  ghcr.io/openhands/agent-server:1.28.0-python

# 2. Canvas pointed at the container.
VITE_BACKEND_BASE_URL=http://localhost:8010 npm run dev:frontend

How credentials reach a containerized agent

In onboarding's Set up credentials step, the credentials you enter are saved as global secrets in the agent-server's secret store (as usual). The start request then references each as a LookupSecret — uniformly for ACP and non-ACP — and the agent-server resolves the value back from its own store at spawn time. For ACP this resolution runs off the event loop (software-agent-sdk#3510), so the loopback fetch does not self-deadlock. The SDK's acp_file_secrets defaults then:

• materialise CODEX_AUTH_JSON back to auth.json under CODEX_HOME and point Codex at it;
• materialise GOOGLE_APPLICATION_CREDENTIALS_JSON to a file referenced by GOOGLE_APPLICATION_CREDENTIALS and route Gemini through Vertex AI;
• export the rest (CLAUDE_CODE_OAUTH_TOKEN, project/location, API keys) as env vars for the CLI.

Canvas just sends the secrets — it does not hand-roll the file materialisation. The npx -y <pkg> command is rewritten to the pinned pre-installed binary inside the container by the SDK, so no command change is needed.

[!IMPORTANT] Do not set ANTHROPIC_BASE_URL alongside the Claude OAuth token. An inherited LiteLLM base URL silently breaks the token's bearer auth (it routes the request away from Anthropic). Canvas never derives a base-URL secret from your LLM settings — but a base URL you save yourself rides along on every start request like any other saved secret, which is why the credential forms warn when both are set. Only set it deliberately, and not with the OAuth path.

[!IMPORTANT] Gemini Vertex needs a fresh ADC. Run gcloud auth application-default login before copying ~/.config/gcloud/application_default_credentials.json — a stale token surfaces as invalid_rapt, which is a credential problem, not a Canvas bug.

[!NOTE] Pick a non-flash Gemini model. gemini-cli 0.45.x re-resolves any *-flash model id at generation time to its current default flash (e.g. gemini-2.5-flash silently ran gemini-3-flash, which 404s on projects that don't serve it — software-agent-sdk#3532). Only a non-flash id sticks, so Canvas preselects gemini-2.5-pro. If a Gemini turn fails with Publisher Model … was not found, check the selected model isn't a flash id.

Per-conversation isolation

Concurrent same-provider conversations in one container share a HOME, so they can race on the CLI's auth/config/lock files. The SDK supports opting into a per-conversation data dir (acp_isolate_data_dir, software-agent-sdk#3492), but the released @openhands/typescript-client does not yet expose it on ACPAgentSettings, so Canvas can't send it without risking a validation error on older servers. This is tracked as a follow-up (agent-canvas#1019); cloud grouping isolation is separate (agent-canvas#1016).

Switching agent or model later

Open Settings → Agent at any time:

• Agent — switch between OpenHands and ACP.
• Preset — pick a built-in provider (Claude Code, Codex, Gemini CLI) or Custom to point at any other ACP server.
• Command — the command line used to spawn the subprocess. Selecting a preset fills this in; editing it to match another preset re-detects that provider. API keys are not entered here — they live in the Secrets panel.
• Model — choose a suggested model for the provider or enter a custom model override. Built-in providers save a concrete model rather than leaving it blank.

Saving writes an agent_settings_diff (agent_kind, acp_server, acp_command, acp_model) to PATCH /api/settings. A running conversation keeps the agent it started with; the new choice applies to conversations you start afterward.

Custom ACP servers

Any stdio ACP server works: choose Custom in Settings → Agent and enter its launch command. Custom servers have no curated model list, so enter the model ID the server expects (if any) as a custom model. Pass credentials by adding the env vars the server reads as global secrets under Settings → Secrets.