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mel is built agents-first: an AI agent with shell access can create canvases and run generations without any human in the loop. Three properties make it reliable to automate.
  • JSON on stdout, always. Success is structured JSON; there are no prompts, spinners, or color codes to parse around.
  • Deterministic exit codes. Branch on the exit code alone — 0 success, 3 auth, 4 timeout — without reading text.
  • Structured errors with fixes. Every error is JSON on stderr with a code and a suggestion naming the command to recover.

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Headless authentication

Set the key as an environment variable — nothing is written to disk and no mel auth login step is needed: 
export MEL_API_KEY=mel_...
export MEL_BASE_URL=https://api.melius.com   # optional; the default
The key’s own team is used automatically. To act on a different team the user is a member of, set MEL_TEAM_ID — your role is scoped per team, just like the app. In a sandbox, allow network egress to api.melius.com (or *.melius.com).

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Parsing output

Capture ids with --fields <field> --text, or pipe full JSON through jq: 
# Just the id, for a shell variable
CANVAS=$(mel canvas create "$PROJECT" --title "Ad set" --fields id --text)

# Full object → jq
mel canvas content "$CANVAS" | jq '.nodes[] | {id, type: .nodeType, status}'

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Branching on exit codes

mel run wait "$RUN"
case $? in
  0) mel run download "$RUN" ;;                 # finished → get the output
  4) echo "still running, will re-check" ;;     # timeout → poll again later
  *) mel run get "$RUN" ;;                       # failed → inspect the error
esac

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CLI or MCP?

Both let an agent drive Melius, over the same backend and API keys — choose by how your agent runs:
Use the…When your agent…
CLI (mel)Has shell access — a coding agent, a CI job, or a sandbox with a terminal. It chains commands and parses JSON.
MCP serverRuns in a chat client that speaks MCP (Claude Desktop, Claude Code) and calls tools directly, with no shell.
If your agent already has a terminal, mel is usually the simplest path — one install, MEL_API_KEY, and it’s driving the canvas.

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Next steps

Command reference

Every command, flag, exit code, and error shape.

MCP server

Connect a chat-based agent over the Model Context Protocol.
Last modified on July 1, 2026