# List Meetings — Read AI

> Retrieves a paginated list of meetings from Read AI, ordered by most recent first. Use this to browse meeting history or to find a specific meeting before calling Get Meeting for full details. Supports date range filtering via Unix…

- Key: `read_ai-list-meetings`
- Type: Action (Read-only)
- Version: 0.1.1
- App: Read AI (`read_ai`) — https://pipedream.com/apps/read-ai.md
- This page (HTML): https://pipedream.com/apps/read-ai/actions/list-meetings
- Hints: read-only · open-world
- Source: https://github.com/PipedreamHQ/pipedream/blob/master/components/read_ai/actions/list-meetings/list-meetings.mjs

## Description

Retrieves a paginated list of meetings from Read AI, ordered by most recent first. Use this to browse meeting history or to find a specific meeting before calling **Get Meeting** for full details. Supports date range filtering via Unix millisecond timestamps. Returns meeting metadata including ID, title, participants, platform (Zoom/Teams/Google Meet), start time, and duration. Use the expand options to include richer content (summary, action items, transcript, etc.) directly in the listing — note that active meetings will have limited or no data for expanded fields, as these are generated after a meeting concludes. When `has_more` is `true` in the response, pass the `id` of the last meeting in the `data` array to the `cursor` parameter to retrieve the next page. To convert a human date to Unix ms, multiply Unix seconds by 1000 (e.g. 7 days ago = `Date.now() - 7*24*60*60*1000`). [See the documentation](https://support.read.ai/hc/en-us/articles/49381161088659-API-Reference#h_01KJ7HW2RMF7VS2EHTXAWS4BJ7)

## Props

| Prop | Type | Required | Description |
|---|---|---|---|
| `startTimeMs` | `integer` | No | Filter meetings that started at or after this Unix timestamp in milliseconds. Example: 1700000000000 for a fixed date, or compute relative times like 7 days ago. |
| `endTimeMs` | `integer` | No | Filter meetings that started at or before this Unix timestamp in milliseconds. Example: 1700000000000. |
| `limit` | `integer` | Yes | Number of meetings to return. Maximum is 10. |
| `cursor` | `string` | No | Cursor from a previous list response (nextCursor) to retrieve the next page of results. |
| `includeSummary` | `boolean` | No | Include the AI-generated meeting summary and chapter summaries. |
| `includeActionItems` | `boolean` | No | Include extracted action items with implied owners. |
| `includeTranscript` | `boolean` | No | Include the full word-for-word transcript with speaker attribution. Can be very large for long meetings. |
| `includeKeyQuestions` | `boolean` | No | Include key questions flagged by AI during the meeting. |
| `includeTopics` | `boolean` | No | Include identified discussion topics and subject areas. |
| `includeMetrics` | `boolean` | No | Include speaker engagement metrics: talk time, interruptions, engagement scores. |
| `includeRecordingDownload` | `boolean` | No | Include a presigned URL to download the meeting recording. |

## Run it

**MCP**

```ts
import { Client } from "@modelcontextprotocol/sdk/client/index.js"
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp.js"
import { PipedreamClient } from "@pipedream/sdk"

const pd = new PipedreamClient({
  projectId: process.env.PIPEDREAM_PROJECT_ID!,
  clientId: process.env.PIPEDREAM_CLIENT_ID!,
  clientSecret: process.env.PIPEDREAM_CLIENT_SECRET!,
  projectEnvironment: "production",
})

const accessToken = await pd.rawAccessToken

const transport = new StreamableHTTPClientTransport(
  new URL("https://remote.mcp.pipedream.net/v3"),
  {
    requestInit: {
      headers: {
        Authorization: `Bearer ${accessToken}`,
        "x-pd-project-id": process.env.PIPEDREAM_PROJECT_ID!,
        "x-pd-environment": "production",
        "x-pd-external-user-id": "{external_user_id}", // any stable ID for this user in your system
        "x-pd-app-slug": "read_ai",
      },
    },
  },
)

const mcp = new Client({ name: "my-agent", version: "1.0.0" })
await mcp.connect(transport)

const { tools } = await mcp.listTools()

// listTools() hands your model this tool's input schema, so it can
// fill the arguments itself:
const result = await mcp.callTool({
  name: "read_ai-list-meetings",
  arguments: {
    startTimeMs: 10,
    endTimeMs: 10,
  },
})
```

**TypeScript**

```ts
import { PipedreamClient } from "@pipedream/sdk"

const pd = new PipedreamClient({
  projectId: process.env.PIPEDREAM_PROJECT_ID!,
  clientId: process.env.PIPEDREAM_CLIENT_ID!,
  clientSecret: process.env.PIPEDREAM_CLIENT_SECRET!,
  projectEnvironment: "production",
})

const result = await pd.actions.run({
  id: "read_ai-list-meetings",
  externalUserId: "{external_user_id}", // any stable ID for this user in your system
  configuredProps: {
    read_ai: { authProvisionId: "apn_xxxxxxx" },
    startTimeMs: 10,
    endTimeMs: 10,
  },
})

console.log(result)
```

**cURL**

```bash
curl -X POST https://api.pipedream.com/v1/connect/{project_id}/actions/run \
  -H "Content-Type: application/json" \
  -H "X-PD-Environment: production" \
  -H "Authorization: Bearer {access_token}" \
  -d '{
    "external_user_id": "{external_user_id}",
    "id": "read_ai-list-meetings",
    "configured_props": {
      "read_ai": { "authProvisionId": "apn_xxxxxxx" },
      "startTimeMs": 10,
      "endTimeMs": 10
    }
  }'
```

---

- App: https://pipedream.com/apps/read-ai.md · All apps: https://pipedream.com/apps