Datumbox MCP Server

MCP server for Datumbox, a machine learning platform specialized in Natural Language Processing (NLP).

• Category: AI Integration – MCP Servers
• Vendor / Brand: Datumbox
• Slug: datumbox-mcp-server

Overview

The Datumbox MCP Server exposes Datumbox’s machine learning and NLP capabilities through the Model Context Protocol (MCP), allowing compatible chat or agent clients to connect to Datumbox via a standardized server endpoint.

The server is operated via Pipedream Connect and is accessible through a static URL that can be used across different MCP-compatible clients.

Features

• MCP-compatible endpoint

  • Provides a static MCP server URL that works with any MCP client:
    • https://mcp.pipedream.net/v2
  • Designed to be added to chat or agent applications that support MCP.

• Datumbox NLP integration

  • Connects clients to Datumbox, a platform focused on natural language processing and machine learning (specific NLP tools are not listed in the provided content, but the integration is oriented around NLP use cases).

• Authentication handled on add

  • Authentication occurs when you add the MCP server to your application; the same URL can be reused across clients.

• Client-agnostic setup

  • Instructions are available for multiple chat clients (via the “select your chat client” flow) so the same server can be integrated into different tools.

• Central configuration documentation

  • Full configuration details and setup steps are available on a dedicated Configuration page (linked from the item page).

Setup

1. Use the static MCP server URL:
   https://mcp.pipedream.net/v2
2. Add this URL to your MCP-compatible chat or agent client.
3. Follow the client-specific instructions (via the “select your chat client” flow) to complete authentication and configuration.
4. Optionally consult the full Configuration page for detailed parameters and usage patterns.

Pricing

The provided content does not list any specific pricing or plans for the Datumbox MCP Server or Datumbox itself. Pricing information is not available in the supplied material.

Tags

• nlp
• machine-learning
• api