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OpenAI Web Search MCP Server

by tiovikram

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.

-
security - not tested
A
license - permissive license
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quality - not tested

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