Read Otter.ai channels, conversations, transcripts, action items, insights and outlines, download meeting audio, and import calls from a URL — over Otter's Enterprise Public API.
Otter.ai ships in the w6w first-party pack. It declares 7 actions, 2 health checks, and the host runs its code in a sandbox that never sees the credential.
io.w6w.otterOtter.ai is an AI meeting assistant that records, transcribes and summarizes conversations, then turns them into searchable transcripts, abstractive summaries, action items, topic insights and outlines. This app reads that output into a workflow: list and search conversations, fetch one with any combination of its generated action items, insights, outline or full transcript, download the meeting’s MP3, and organize by Channel (Otter’s shared-folder concept) and workspace member.
A conversation-create action covers the other direction — importing a publicly downloadable audio or video URL as a new Otter conversation, the documented path for pulling calls in from a dialer or another recording source.
Otter’s Public API is gated to Enterprise workspaces only; a Free, Pro or Business account has no access to any endpoint this app calls, and Auth.test reports that distinctly from a bad key. Real-time updates are documented as a separate Webhooks surface rather than anything pollable here — out of scope for this app’s Actions, which only cover reads and the one documented write.
Three routes to the same 7 actions. The Workflow tab is generated from Otter.ai's own manifest and carries its real ids, so it is copy-pasteable; the Code and CLI examples are the same call for any action on any app, so every app-specific value in them is a blank you fill in.
channel-members-list List all members of a channel, in alphabetical order by member name.
conversation-audio-get Get the MP3 audio download link for a specific conversation.
conversation-create Import a publicly downloadable audio or video URL as a new Otter conversation — for pulling calls in from a Dialer or another recording source.
conversation-get Get a conversation's summary and details, plus the requested relationships (action items, insights, outline, transcript).
conversation-list List conversations for the authenticated user, most recent first. Cursor-paginated.
workspace-get Get the authenticated user's Otter workspace — id, name, owner, member count, handle and type.
A workflow step names the app and the action, and the editor fills in the
connection when you pick one. This is the Step shape from the
workflow spec, carrying Otter.ai's real ids.
{
"manifestVersion": "2",
"name": "otter-example",
"steps": [
{
"id": "channel-members-list",
"uses": {
"app": "io.w6w.otter",
"action": "channel-members-list",
"connection": "conn_YOUR_CONNECTION_ID"
},
"with": {
"channelId": "<channelId>"
}
}
]
}channel-members-list channel-list conversation-audio-get conversation-create conversation-get +2 more actions available
Every app-specific value here is a blank you have to fill in. An
app action is reached through the connection that authenticates it, so the
address is a connection id, not the app id — and connections belong to your account,
so a public page cannot know yours. Create one for Otter.ai, then fill in
the three blanks: conn_YOUR_CONNECTION_ID, the action key, and the
parameters that action declares. The call itself is real — the shape is transcribed
from the studio's own snippet builder, which prints the same kind of blanks — but
nothing in it is specific to Otter.ai. The Workflow tab is where this app's
real ids are.
npm install @w6w/sdkyarn add @w6w/sdkpnpm add @w6w/sdkdeno add npm:@w6w/sdkimport { W6wClient, isActionRun } from "@w6w/sdk";
// Reads W6W_BASE_URL and W6W_TOKEN from the environment when omitted.
const client = new W6wClient();
const envelope = await client.run({
urn: "conn_YOUR_CONNECTION_ID",
action: "channel-members-list",
payload: {
channelId: "<value>",
},
});
if (isActionRun(envelope)) console.log(envelope.value); npm install -g @w6w/cli w6w run conn_YOUR_CONNECTION_ID --action channel-members-list --payload '{"channelId":"<value>"}' Give an AI agent Otter.ai — without giving it Otter.ai's credentials. One MCP endpoint exposes every app, function and workflow the caller is entitled to, as tools it can discover and run. Access is granted per team while we onboard.
One tool call{
"name": "w6w_invoke",
"arguments": {
"ref": "app:io.w6w.otter#channel-members-list",
"input": {
"channelId": "<channelId>"
}
}
}
Every tool names its target with a single ref. The
app: form above doesn't name a connection at all — the
host resolves which of the caller's Otter.ai connections to sign
with, and refuses rather than guesses when the answer is ambiguous.
The token is attached host-side, at the moment of the call. It is never a tool argument, never in the model's context, and never in a transcript — so a prompt injection has nothing to exfiltrate.
Tools are derived per end user from what that person has actually connected and is entitled to — not one shared bot identity carrying the union of everyone's access.
Multi-step work runs on the workflow engine and returns a run handle the agent can poll — retries, branching and state survive the conversation that started them.
Otter.ai's declared health checks are on the surface too, so an agent can tell "the vendor is down" from "your credential expired" before it burns a retry on either.
The MCP surface is part of the hosted platform. Otter.ai itself is MIT, and the runtime that executes it is source-available (FSL).
Otter.ai declares its own checks, so its health is a property of the app rather than something the host guesses at.
Component status from status.otter.ai, an Atlassian Statuspage. Highlights the 'Public API' component specifically, alongside the vendor's own page-level roll-up.