# Analyze Text — Speak AI

> Retrieve the insights Speak AI generated for a text note: sentiment, keywords and named entities. Takes the media ID of a text note that already exists in Speak AI. See the documentation.

- Key: `speak_ai-analyze-text`
- Type: Action (Read-only)
- Version: 0.0.4
- App: Speak AI (`speak_ai`) — https://pipedream.com/apps/speak-ai.md
- This page (HTML): https://pipedream.com/apps/speak-ai/actions/analyze-text
- Hints: read-only · open-world
- Source: https://github.com/PipedreamHQ/pipedream/blob/master/components/speak_ai/actions/analyze-text/analyze-text.mjs

## Description

Retrieve the insights Speak AI generated for a text note: sentiment, keywords and named entities. Takes the media ID of a text note that already exists in Speak AI. [See the documentation](https://docs.speakai.co/api/text/#get-text-insight-media-id).

## Props

| Prop | Type | Required | Description |
|---|---|---|---|
| `folderId` | `string` | Yes | A Speak AI folder ID, e.g. 905c208f1c07. The folder to upload to, or to retrieve files from. Returned as folderId by List Folder ID Options Options are loaded from the connected account. |
| `mediaId` | `string` | Yes | A Speak AI media ID, e.g. f8eb3c22bec3. Returned as mediaId by Upload Media and by every media trigger in this app Options are loaded from the connected account. |

## 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": "speak_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: "speak_ai-analyze-text",
  arguments: {
    folderId: "Folder ID",
    mediaId: "Media ID",
  },
})
```

**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: "speak_ai-analyze-text",
  externalUserId: "{external_user_id}", // any stable ID for this user in your system
  configuredProps: {
    speak_ai: { authProvisionId: "apn_xxxxxxx" },
    folderId: "Folder ID",
    mediaId: "Media ID",
  },
})

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": "speak_ai-analyze-text",
    "configured_props": {
      "speak_ai": { "authProvisionId": "apn_xxxxxxx" },
      "folderId": "Folder ID",
      "mediaId": "Media ID"
    }
  }'
```

---

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