Gumloop MCP Server

MCP Server for Gumloop's API, enabling AI models to manage and execute automations through a standardized interface.

Features

• Flow Management: Start automations and monitor their execution status

• Workspace Discovery: List available workbooks and saved automation flows

• Input Schema Retrieval: Get detailed information about required inputs for flows

• File Operations: Upload and download files used in automations

• Context-Aware Execution: Run automations with input parameters specific to user needs

Related MCP server: AI Agent Marketplace Index Search

Tools

startAutomation

Initiates a new flow run for a specific saved automation.

Inputs:

• user_id (string): The ID for the user initiating the flow

• saved_item_id (string): The ID for the saved flow

• project_id (string, optional): The ID of the project within which the flow is executed

• pipeline_inputs (array, optional): List of inputs for the flow

  • input_name (string): The 'input_name' parameter from your Input node

  • value (string): The value to be passed to the Input node

Returns: Response with run details including run_id, saved_item_id, workbook_id and URL

retrieveRunDetails

Retrieves details about a specific flow run.

Inputs:

• run_id (string): ID of the flow run to retrieve

• user_id (string, optional): The ID for the user initiating the flow

• project_id (string, optional): The ID of the project within which the flow is executed

Returns: Response with run details including state, outputs, timestamps, and logs

listSavedFlows

Retrieves a list of all saved flows for a user or project.

Inputs:

• user_id (string, optional): The user ID for which to list items

• project_id (string, optional): The project ID for which to list items

Returns: Response with list of saved flows and their metadata

listWorkbooks

Retrieves a list of all workbooks and their associated saved flows.

Inputs:

• user_id (string, optional): The user ID for which to list workbooks

• project_id (string, optional): The project ID for which to list workbooks

Returns: Response with list of workbooks and their associated saved flows

retrieveInputSchema

Retrieves the input schema for a specific saved flow.

Inputs:

• saved_item_id (string): The ID of the saved item for which to retrieve input schemas

• user_id (string, optional): User ID that created the flow

• project_id (string, optional): Project ID that the flow is under

Returns: Response with list of input parameters for the flow

uploadFile

Uploads a single file to the Gumloop platform.

Inputs:

• file_name (string): The name of the file to be uploaded

• file_content (string): Base64 encoded content of the file

• user_id (string, optional): The user ID associated with the file

• project_id (string, optional): The project ID associated with the file

Returns: Response with success status and file name

uploadMultipleFiles

Uploads multiple files to the Gumloop platform in a single request.

Inputs:

• files (array): Array of file objects to upload

  • file_name (string): The name of the file to be uploaded

  • file_content (string): Base64 encoded content of the file

• user_id (string, optional): The user ID associated with the files

• project_id (string, optional): The project ID associated with the files

Returns: Response with success status and list of uploaded file names

downloadFile

Downloads a specific file from the Gumloop platform.

Inputs:

• file_name (string): The name of the file to download

• run_id (string): The ID of the flow run associated with the file

• saved_item_id (string): The saved item ID associated with the file

• user_id (string, optional): The user ID associated with the flow run

• project_id (string, optional): The project ID associated with the flow run

Returns: The requested file content

downloadMultipleFiles

Downloads multiple files from the Gumloop platform as a zip archive.

Inputs:

• file_names (array): An array of file names to download

• run_id (string): The ID of the flow run associated with the files

• user_id (string, optional): The user ID associated with the files

• project_id (string, optional): The project ID associated with the files

• saved_item_id (string, optional): The saved item ID associated with the files

Returns: Zip file containing the requested files

Setup

API Key

Create a Gumloop API key with access to the required features:

1. Go to Gumloop Workspace Settings

2. Generate a new API key

3. Copy the generated key

Usage with Claude Desktop

To use this with Claude Desktop, add the following to your claude_desktop_config.json:

Using NPX

{
  "mcpServers": {
    "gumloop": {
      "command": "npx",
      "args": [
        "-y",
        "gumloop-mcp-server"
      ],
      "env": {
        "GUMLOOP_API_KEY": "<YOUR_GUMLOOP_API_KEY>"
      }
    }
  }
}

Using Docker

{
  "mcpServers": {
    "gumloop": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "GUMLOOP_API_KEY",
        "gumloop-mcp-server"
      ],
      "env": {
        "GUMLOOP_API_KEY": "<YOUR_GUMLOOP_API_KEY>"
      }
    }
  }
}

Examples

Starting an Automation

// Start a saved automation flow
const result = await agent.callTool("startAutomation", {
  user_id: "user123",
  saved_item_id: "flow456",
  pipeline_inputs: [
    {
      input_name: "search_query",
      value: "AI automation trends 2025"
    }
  ]
});

Checking Run Status

// Check the status of a running automation
const result = await agent.callTool("retrieveRunDetails", {
  run_id: "run789",
  user_id: "user123"
});

Listing Available Flows

// Get all saved flows for a user
const result = await agent.callTool("listSavedFlows", {
  user_id: "user123"
});

Working with Files

// Upload a file to be used in an automation
const result = await agent.callTool("uploadFile", {
  user_id: "user123",
  file_name: "data.csv",
  file_content: "base64EncodedFileContent..."
});

Response Format

The server returns Gumloop API responses in JSON format. Here's an example for retrieving run details:

{
  "user_id": "user123",
  "state": "RUNNING",
  "outputs": {},
  "created_ts": "2023-11-07T05:31:56Z",
  "finished_ts": null,
  "log": [
    "Starting automation flow...",
    "Processing input parameters...",
    "Executing node 1: Web Scraper..."
  ]
}

Limitations

• API calls are subject to Gumloop's rate limits and usage quotas

• File uploads are limited to the maximum size allowed by Gumloop's API

• Some features may require specific subscription tiers

• The server requires a valid Gumloop API key with appropriate permissions

Build

# Install dependencies
pnpm install

# Build the project
pnpm run build

# Start the server
pnpm start

License

This MCP server is licensed under the MIT License.