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
Tools
startAutomation
Initiates a new flow run for a specific saved automation.
Inputs:
user_id
(string): The ID for the user initiating the flowsaved_item_id
(string): The ID for the saved flowproject_id
(string, optional): The ID of the project within which the flow is executedpipeline_inputs
(array, optional): List of inputs for the flowinput_name
(string): The ‘input_name’ parameter from your Input nodevalue
(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 retrieveuser_id
(string, optional): The ID for the user initiating the flowproject_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 itemsproject_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 workbooksproject_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 schemasuser_id
(string, optional): User ID that created the flowproject_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 uploadedfile_content
(string): Base64 encoded content of the fileuser_id
(string, optional): The user ID associated with the fileproject_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 uploadfile_name
(string): The name of the file to be uploadedfile_content
(string): Base64 encoded content of the file
user_id
(string, optional): The user ID associated with the filesproject_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 downloadrun_id
(string): The ID of the flow run associated with the filesaved_item_id
(string): The saved item ID associated with the fileuser_id
(string, optional): The user ID associated with the flow runproject_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 downloadrun_id
(string): The ID of the flow run associated with the filesuser_id
(string, optional): The user ID associated with the filesproject_id
(string, optional): The project ID associated with the filessaved_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:
- Go to Gumloop Workspace Settings
- Generate a new API key
- 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.
Gumloop Automation Server
Project Details
- tiovikram/gumloop-mcp
- MIT License
- Last Updated: 4/25/2025
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