# AlgoDocs — Pipedream Connect

> Intelligent Document Processing - AI-Powered Document Data Extraction

- API slug: `algodocs` (use in MCP headers and tool keys)
- Auth: API key (Pipedream-managed)
- Categories: Artificial Intelligence (AI)
- Website: https://www.algodocs.com/
- This page (HTML): https://pipedream.com/apps/algodocs
- Tools: 4 actions · 2 triggers

## Connect via MCP (recommended)

- Endpoint: `https://remote.mcp.pipedream.net/v3`
- Headers: `Authorization: Bearer <token>` · `x-pd-project-id` · `x-pd-environment` · `x-pd-external-user-id` · `x-pd-app-slug: algodocs`

```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": "algodocs",
      },
    },
  },
)

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

const { tools } = await mcp.listTools()

// e.g. run List Documents:
const result = await mcp.callTool({
  name: "algodocs-list-documents",
  arguments: {
    extractorId: "Extractor ID",
    folderId: "Folder ID",
  },
})
```

Docs: [MCP guide](https://pipedream.com/docs/connect/mcp/developers.md)

## API proxy

For a AlgoDocs endpoint with no pre-built tool, the proxy forwards your request with the connected user's credentials attached.

```bash
# The path segment is the target URL, URL-safe base64 encoded:
# https://api.algodocs.com/v1/me

curl "https://api.pipedream.com/v1/connect/{project_id}/proxy/aHR0cHM6Ly9hcGkuYWxnb2RvY3MuY29tL3YxL21l?external_user_id={external_user_id}&account_id=apn_xxxxxxx" \
  -H "Authorization: Bearer {access_token}" \
  -H "x-pd-environment: production"
```

Docs: [API proxy guide](https://pipedream.com/docs/connect/api-proxy.md)

## SDK

```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: "algodocs-list-documents",
  externalUserId: "{external_user_id}", // any stable ID for this user in your system
  configuredProps: {
    algodocs: { authProvisionId: "apn_xxxxxxx" },
    extractorId: "Extractor ID",
    folderId: "Folder ID",
  },
})
```

Docs: [Managed auth guide](https://pipedream.com/docs/connect/managed-auth/quickstart.md) · [Tools guide](https://pipedream.com/docs/connect/components.md)

## Actions (4)

### `algodocs-list-documents` — List Documents (Read-only)

Lists documents for a given extractor by reading extraction records (GET /v1/extracted_data/{extractorId}) and returning their documentId and fileName, deduplicated by documentId. AlgoDocs has no dedicated documents endpoint, so this action derives the document list from extracted data. Use it to…

Full schema: https://pipedream.com/apps/algodocs/actions/list-documents.md

### `algodocs-list-extractors` — List Extractors (Read-only)

Lists all extractors in the authenticated AlgoDocs account (GET /v1/extractors). Each extractor includes at least id and name. Use this to discover a valid extractorId before running Upload File or List Documents. See the documentation.

Full schema: https://pipedream.com/apps/algodocs/actions/list-extractors.md

### `algodocs-list-folders` — List Folders (Read-only)

Lists all folders in the authenticated AlgoDocs account (GET /v1/folders). Each folder includes at least id and name. Use this to discover a valid folderId before running Upload File. See the documentation.

Full schema: https://pipedream.com/apps/algodocs/actions/list-folders.md

### `algodocs-upload-file` — Upload File (Write)

Uploads a local file to an AlgoDocs folder for processing by a specific extractor via multipart/form-data (POST /v1/document/upload_local/{extractorId}/{folderId}). Returns the created document record including its id and upload metadata. Run List Extractors to find a valid extractor ID and List…

Full schema: https://pipedream.com/apps/algodocs/actions/upload-file.md

## Triggers (2)

### `algodocs-new-extracted-data` — New Extracted Data (Polling)

Emit new event for each newly extracted data record for a given AlgoDocs document (polls GET /v1/extracted_data/{documentId}). Each extraction record's stable id is used for deduplication. Run the List Documents action to find a valid document ID before configuring this source. An optional filter…

Full schema: https://pipedream.com/apps/algodocs/triggers/new-extracted-data.md

### `algodocs-new-table-row-extracted` — New Table Row Extracted (Polling)

Emit new event for each individual table row extracted from an AlgoDocs document (polls GET /v1/extracted_data/{documentId}). AlgoDocs represents a record's extracted data as a flat object, with any table/repeating field appearing as an array-valued property (e.g. data.LineItems). Unlike New…

Full schema: https://pipedream.com/apps/algodocs/triggers/new-table-row-extracted.md

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- All apps: https://pipedream.com/apps — index: https://pipedream.com/llms.txt
- Pipedream docs for agents: https://pipedream.com/docs/llms.txt