Unity AI Gateway Coding CLI (ucode)

ucode is a lightweight launcher for running Codex, Claude Code, Gemini CLI, OpenCode, GitHub Copilot CLI, and Pi through Databricks.

Requirements

• Python 3.12+ — install with uv (uv.astral.sh)
• npm if tool CLIs need to be installed automatically

Installation

uv tool install git+https://github.com/databricks/ucode

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Usage

Just run the tool you want:

ucode codex      # OpenAI Codex
ucode claude     # Claude Code
ucode gemini     # Gemini CLI
ucode opencode   # OpenCode
ucode copilot    # GitHub Copilot CLI
ucode pi         # Pi
ucode cursor     # Cursor Agent (MCP only — see below)

On first launch, ucode will prompt for your Databricks workspace URL, authenticate, and configure that tool automatically. Subsequent launches go straight to the agent.

Pass flags directly to the underlying tool:

ucode claude -r          # resume last session
ucode codex --full-auto

All agents route through Databricks AI Gateway using your workspace credentials — no API keys required.

To configure all tools at once:

ucode configure

To configure specific tools without the picker, pass a comma-separated list:

ucode configure --agents claude,codex

Available agent names are codex, claude, gemini, opencode, copilot, and pi. cursor is also accepted (MCP-only — it registers Databricks MCP servers but configures no models).

To configure without the workspace picker, pass a comma-separated list of workspaces:

ucode configure --workspaces https://first.databricks.com,https://second.databricks.com

When multiple workspaces are provided, ucode logs into and saves state for each workspace. Launch commands such as ucode codex use the first workspace in the list.

Alternatively, pass existing Databricks CLI profiles (from ~/.databrickscfg) instead of workspace URLs — each profile's host supplies the workspace URL:

ucode configure --profiles DEFAULT --agents claude,codex

Auth behaves the same as --workspaces: an OAuth databricks auth login is forced by default.

For CI or headless environments where the profile holds a personal access token (auth_type = pat in ~/.databrickscfg), add --use-pat. It must be combined with --profiles — ucode never picks up a PAT implicitly — and runs no interactive login: the profile's token is used for the whole setup (and by launched agents afterwards), with workspace access verified against the AI Gateway. --skip-validate additionally skips the post-configure test message sent through each agent, so configure only writes config files with the freshly discovered models. Together these make setup fully non-interactive:

ucode configure --profiles DEFAULT --agents claude,codex --use-pat --skip-validate --skip-upgrade

MCP servers (optional)

ucode configure mcp

Add Databricks MCP servers to installed MCP-capable tools: Codex, Claude Code, Gemini CLI, OpenCode, GitHub Copilot CLI, and Cursor Agent. Options are shown in this order:

• Discovered external MCP connections
• Databricks SQL
• Managed Databricks MCPs (Vector Search, UC Functions, etc.)
• Custom MCP server URL

Discovered external MCP connections are listed directly.

Every Databricks MCP server is registered as a local stdio server that runs ucode mcp-proxy — a small bridge (shipped with ucode) between the coding tool and the Databricks streamable-HTTP MCP endpoint. The proxy mints a fresh OAuth token from your Databricks CLI profile on every request, so MCP auth is handled uniformly for every client and never expires mid-session. The coding tool starts and stops the proxy as a child process; there's nothing extra to run.

Cursor is MCP-only: cursor-agent runs models on your own Cursor account, so ucode configures no models for it — it only registers Databricks MCP servers in ~/.cursor/mcp.json (via the same proxy). Include it with ucode configure --agents cursor or pick it in ucode configure mcp, then launch with ucode cursor.

To set up an agent and its MCP server(s) in one command, pass --mcp with fully-qualified service name(s) to ucode configure:

ucode configure --agents claude --mcp system.ai.slack

--mcp also works without --agents for MCP-only clients (it configures just the workspace, then registers the servers); pass a comma-separated list to register several at once.

Skills (optional)

Configure Unity Catalog Skills for your coding tools with ucode configure skills:

# Utility tools only: register the schema-less skills MCP connection, no download.
ucode configure skills

# Download mode: fetch every skill in the schema to disk (and register the connection).
ucode configure skills --location main.default --path /abs/project/dir

# Download a named subset of the schema's skills instead of all of them.
ucode configure skills --location main.default --skill my-skill

# MCP mode: expose the schema's skills as MCP tools instead of downloading.
ucode configure skills --location main.default,ml.prod --mcp

• Bare command (no --location) registers the schema-less skills MCP connection — the cross-schema utility tools only — and downloads nothing. --mcp with no --location does the same.
• Download mode (with --location, no --mcp) writes each skill flat as <leaf>/SKILL.md (plus its bundled files) into both .claude/skills/ and .agents/skills/. --path (an existing absolute directory) is optional; when omitted, skills are written under your home directory. Any pre-existing skill dir prompts before it's overwritten. It then registers a schema-less skills MCP connection, leaving any prior --mcp scope untouched. --skill <name>[,<name>…] narrows the download to the named skills (by leaf name) from the schema instead of all of them; requested names not found in the schema warn and are skipped. --skill requires a single --location, is download-only, and is rejected with --mcp.
• MCP mode (--location … --mcp) sets the connection's location set to exactly <list> (override-only) and rebuilds its ?schema= URL; no files are downloaded and --path is rejected.

Each run prints the registered server, its URL, the configured agents, and its tools, and reminds you to run ucode <agent> (existing agent sessions need a restart before the MCP tools load).

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Other Commands

Command	Description
ucode status	Show current workspace, base URLs, managed config files, and selected models
ucode usage	Show AI Gateway usage summary
ucode revert	Clear saved state and restore backed-up config files
ucode configure --dry-run	Preview config files without writing them
ucode configure --agents claude,codex	Configure specific agents without the interactive picker
ucode configure --workspaces https://first.databricks.com,https://second.databricks.com	Configure workspaces without the interactive picker
ucode configure --profiles DEFAULT	Configure using existing Databricks CLI profiles (hosts come from ~/.databrickscfg)
ucode configure --profiles DEFAULT --use-pat	Authenticate with the profile's personal access token — no browser login
ucode configure --skip-validate	Write configs without sending a test message through each agent
ucode configure --agents claude --mcp system.ai.slack	Configure an agent and register its Databricks MCP server(s) in one command
ucode configure skills	Register the skills MCP connection (utility tools only); no skills download
ucode configure skills --location main.default [--path <dir>]	Download a schema's skills to disk (under <dir>, or your home dir) and register a schema-less skills MCP connection
ucode configure skills --location main.default --skill my-skill	Download only the named skill(s) from a schema (comma-separated for several)
ucode configure skills --location main.default --mcp	Expose a schema's skills as MCP tools (override-only) instead of downloading

Managed Local Files

ucode manages these files:

File	Tool
~/.codex/config.toml	Codex
~/.claude/settings.json	Claude Code
~/.gemini/.env	Gemini CLI
~/.config/opencode/opencode.json	OpenCode
~/.copilot/.env	GitHub Copilot CLI
~/.pi/agent/models.json	Pi
~/.cursor/mcp.json	Cursor Agent (MCP servers only)

Existing files are backed up before being overwritten. ucode revert restores backups.

Documentation

• Databricks AI Gateway overview
• Databricks AI Gateway coding agent integration
• Databricks CLI authentication
• Monitor AI Gateway usage

Contributing

Contributions are welcome.

Getting started

git clone https://github.com/databricks/ucode
cd ucode
uv sync

Development workflow

1. Create a feature branch off main.

2. Make your changes — keep them scoped to the requested behavior.

3. Run the test suite before pushing:

   uv run pytest          # unit tests
   uv run ruff check .    # lint

4. For end-to-end testing against a real workspace:

   UCODE_TEST_WORKSPACE=<db_workspace_url> uv run pytest tests/test_e2e.py -v

5. Open a pull request against main.

Adding a new agent

• Add src/ucode/agents/<name>.py with at least write_tool_config, launch, default_model, and validate_cmd.
• Register it in src/ucode/agents/__init__.py.
• Add focused tests under tests/.

Security

Please report security vulnerabilities to security@databricks.com rather than opening a public issue.

License

See LICENSE.md and NOTICE.md.