Waniwani SDK — Build MCP funnels

@waniwani/cli is the official command-line tool for Waniwani. It wires a local repo to a Waniwani agent, runs your MCP server locally against the hosted playground, and removes the manual steps of provisioning GitHub, Vercel, and API keys. The CLI is optional. @waniwani/sdk works on its own — the CLI is the fastest way to skip the dashboard for project setup and local development.

Install

bun add -g @waniwani/cli

pnpm add -g @waniwani/cli

npm install -g @waniwani/cli

yarn global add @waniwani/cli

Requires Node.js 20 or later.

Quickstart

waniwani login     # browser-based OAuth2 PKCE
waniwani connect   # pick an org + agent, writes waniwani.json
waniwani dev       # run local MCP, open playground bridged to localhost

Three commands. Your local MCP server is now reachable from ChatGPT, Claude, and Cursor through the Waniwani playground, with no tunnel setup.

Commands

Command	What it does
`waniwani login`	Browser-based OAuth2 PKCE. Stores tokens in `.waniwani/settings.json`.
`waniwani logout`	Clear local credentials.
`waniwani connect`	Pick an org, pick or create an agent, write the binding to `waniwani.json`.
`waniwani dev`	Run your MCP locally and open the Waniwani playground against it.

waniwani login [--no-browser] [--json]

Runs the OAuth2 PKCE flow: spins up a local callback server on port 54321, opens your browser to app.waniwani.ai, exchanges the code for an access token, and persists access + refresh tokens to .waniwani/settings.json in the current directory. If you’re already logged in with an expired token, it auto-refreshes and exits. Pass --no-browser to print the URL instead of launching a browser (useful on headless machines).

logout

waniwani logout [--json]

Clears the stored auth tokens. Keeps non-auth config (like apiUrl) intact. No-op if you’re already logged out.

connect

waniwani connect

Interactive only. Walks you through:

Pick an organization. If you’re in one org, it’s auto-selected.
Pick or create an agent. Either select an existing project, create a new managed agent (Waniwani provisions a GitHub repo + Vercel project from the MCP distribution template with API keys pre-wired), or create a new external agent (you host the MCP server; the CLI gives you a production API key to set as WANIWANI_API_KEY).
Write the binding. Writes waniwani.json at the repo root with $schema, orgId, and projectId. If the file already exists, the CLI merges the keys in; if the shape isn’t recognized, it prints the snippet for you to paste. If a legacy waniwani.config.ts is present, it’s removed after the JSON file is written.

Re-run anytime to switch the repo to a different agent.

Managed vs external agents

	Managed	External
Where the server runs	Waniwani-hosted Vercel project	Your infra (Docker, Cloudflare Workers, fly.io, etc.)
Source code	Auto-provisioned from mcp-distribution-template	Yours
API key	Pre-configured in the Vercel env	Printed once by the CLI — save it as `WANIWANI_API_KEY`
Deploys on	Push to `main`	Whatever you already use

See Deployment for the full picture.

dev

waniwani dev [-p <port>]

Interactive only. The end-to-end local dev loop:

Ensures you’re logged in (runs login if not) and that waniwani.json has a projectId (runs connect if not).
Detects your package manager (bun / pnpm / yarn / npm) and spawns the dev script with PORT set.
Waits for the local server to bind to the port.
Creates a dev session against the Waniwani API and starts a heartbeat.
Opens the playground at app.waniwani.ai/agents/<projectId>/playground?localMode=1 so chat traffic routes to your local server.
Ctrl-C tears the dev session down cleanly.

Options:

-p, --port <port> — Port the local MCP listens on. Defaults to devPort in waniwani.json, or 3000.

dev runs your existing dev script — it does not start the MCP for you. The script must bind to process.env.PORT.

Global flags

Flag	Description
`--json`	Output as JSON. Supported by `login` and `logout`. Interactive commands (`connect`, `dev`) error out under `--json`.
`--verbose`	Enable verbose logging.
`--version`	Print the CLI version.
`--help`	Print help.

Configuration

Auth & local state — `.waniwani/settings.json`

Per-repo, gitignored. Holds OAuth tokens and the resolved API URL:

{
  "apiUrl": "https://app.waniwani.ai",
  "accessToken": "…",
  "refreshToken": "…",
  "expiresAt": "2026-05-20T12:00:00Z",
  "clientId": "…"
}

Access tokens auto-refresh on 401. Add .waniwani/ to your .gitignore.

Project config — `waniwani.json`

Shared with @waniwani/sdk. waniwani connect writes $schema, orgId, and projectId; other fields are optional and consumed by the SDK and the dev command:

waniwani.json

{
  "$schema": "https://docs.waniwani.ai/waniwani.json",
  "orgId": "org_…",
  "projectId": "proj_…",
  "devPort": 3000
}

The $schema field unlocks autocomplete and validation in editors that support JSON Schema (VS Code, JetBrains, Neovim with LSP). It’s ignored at runtime. Legacy waniwani.config.ts files are still read for now (with a deprecation warning), but new projects should use waniwani.json. Running waniwani connect against a repo that has a .ts file removes it and writes a .json in its place.

Environment variables

Variable	Purpose
`WANIWANI_API_URL`	Override the API base URL. Defaults to `https://app.waniwani.ai`.
`WANIWANI_API_KEY`	Use a long-lived API key instead of OAuth (useful in CI). See API keys.

Resolution order for the API URL: env var → waniwani.json → .waniwani/settings.json → default. For auth: API key → OAuth tokens (with auto-refresh).

Typical workflow

# One-time
bun add -g @waniwani/cli
waniwani login

# Per-project
cd my-mcp-server
waniwani connect              # creates / picks the agent, writes waniwani.json
waniwani dev                  # runs the dev loop bridged to the playground

To start a fresh project, clone the template first:

git clone https://github.com/WaniWani-AI/mcp-distribution-template.git my-mcp-server
cd my-mcp-server
bun install
waniwani connect
waniwani dev

For AI coding agents

If you’re Claude Code, Cursor, or another AI agent setting up Waniwani in a user’s repo:

Confirm the user is in an MCP project (@waniwani/sdk in package.json, or it’s the distribution template). If not, scaffold one with the SDK quickstart first.
Run waniwani login — opens the browser; the user authenticates once.
Run waniwani connect — interactive; ask the user which org / agent they want, or recommend “managed” if they don’t already host.
Run waniwani dev to verify the bridge works.

The CLI is interactive — connect and dev cannot run under --json. Pair it with the agent skill for code generation:

bunx skills add Waniwani-AI/sdk -s waniwani-sdk

The skill teaches your agent the SDK APIs (flows, tracking, widgets, knowledge base). The CLI handles platform wiring. They’re independent — install whichever you need.

Source

npm: @waniwani/cli
GitHub: Waniwani-AI/cli
Issues: github.com/WaniWani-AI/cli/issues

MIT licensed, like the rest of the Waniwani stack.

Get Started

CLI

Compare

Flow engine

Deployment

Waniwani Platform

Tracking & analytics

Knowledge base

Chat widget

Configuration

Reference

Skills & commands

Build a funnel

Changelog

CLI overview

Install

Quickstart

Commands

logout

connect

Managed vs external agents

dev

Global flags

Configuration

Auth & local state — `.waniwani/settings.json`

Project config — `waniwani.json`

Environment variables

Typical workflow

For AI coding agents

Source

​Install

​Quickstart

​Commands

​login

​logout

​connect

​Managed vs external agents

​dev

​Global flags

​Configuration

​Auth & local state — .waniwani/settings.json

​Project config — waniwani.json

​Environment variables

​Typical workflow

​For AI coding agents

​Source

Install

Quickstart

Commands

login

logout

connect

Managed vs external agents

dev

Global flags

Configuration

Auth & local state — `.waniwani/settings.json`

Project config — `waniwani.json`

Environment variables

Typical workflow

For AI coding agents

Source