@runchat/cli is a command-line interface for Runchat. It exposes the same canvas + workflow toolset as the MCP server — all commands (list_runchats, create_prompt_node, run_nodes etc) run from the shell, a script, or a CI job without an MCP client. Often the quickest way for a coding agent to build a workflow on its own.
The CLI is self-describing. It lists its tools and reads each tool’s parameters live from the server.
Install
@runchat/cli; the installed command is runchat. Requires Node.js ≥ 18.
Authenticate
The CLI authenticates with a Runchat API key (or an OAuth access token: auth.md).1
Create a key
Sign in at runchat.com, open the account menu → Get Runchat API key, and then create a new key or copy an existing one.
2
Provide it to the CLI
Any of these work, highest precedence first:
3
Verify
Tool and command discovery
You can list available tools (broadcast from the MCP server) and get help with the following commands:
Add
--refresh to force-update the cached tool list. Run guide first when building a workflow. This explains node types, the create → connect → organize → run order, choosing models, code nodes, and publishing.
Quickstart
run_nodes and execute_tool consume credits, just like in the app. Confirm
before running anything with real cost.Passing arguments
Arguments are plain--flags, and values are smart-typed — numbers, booleans, and JSON arrays/objects are parsed; everything else stays a string:
--model gpt-5.5 → "gpt-5.5") and id-like values are preserved (--x 007 → "007"). Dashes and underscores in argument names are interchangeable (--runchat-id == --runchat_id).
Pass the whole argument object at once with --json (individual --flags override its keys):
@:
Output & exit codes
Results print as pretty JSON. Use--raw for the server’s exact text — handy for piping into jq:
Configuration
The config file lives at
%APPDATA%\runchat\config.json (Windows) or ~/.config/runchat/config.json (macOS/Linux) and stores your API key.
Use it from an agent
The CLI ships anAGENTS.md so coding agents can drive it without prior knowledge: set RUNCHAT_API_KEY, run runchat guide then runchat tools, read runchat <tool> --help as needed, and branch on the exit codes above.
Related
MCP Server
Connect Claude, ChatGPT, or Cursor to your canvas over the Model Context
Protocol.
Canvas API
The same operations as a plain REST API.