Why should I use RUBE_SEARCH_TOOLS first?

Datagma's tool schemas may change; calling search first ensures Claude uses the most current input parameters and tool slugs for successful execution.

What does the Datagma Automation skill do?

It allows Claude Code to interact with Datagma's sales intelligence tools to search for leads and enrich contact data automatically.

Is a Rube account required?

You simply need to add the Rube MCP endpoint (https://rube.app/mcp) to your Claude configuration to start using the Datagma toolkit.

Can this skill handle large lists of leads?

Yes, it supports pagination and bulk operations through the RUBE_REMOTE_WORKBENCH and RUBE_MULTI_EXECUTE_TOOL commands.

Do I need to provide a Datagma API key immediately?

No, the skill uses Rube MCP to manage connections. You will be prompted to follow an auth link via RUBE_MANAGE_CONNECTIONS to connect your Datagma account.

Datagma Automation

Name: Datagma Automation
Author: EricGrill

byEricGrill

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Marketing Automation

Automates lead enrichment and sales intelligence workflows using the Datagma toolkit via Rube MCP.

This skill enables Claude to perform sophisticated Datagma operations, including lead discovery, contact enrichment, and sales intelligence gathering. By leveraging the Composio Datagma toolkit through Rube MCP, it provides a standardized framework for discovering tool schemas, managing secure connections, and executing multi-step data workflows. It is ideal for developers and growth teams looking to integrate high-quality prospect data directly into their AI-driven sales and marketing automation pipelines.

Key Features

01Dynamic tool discovery for up-to-date Datagma API schemas

02Session-based workflow management for consistent data handling

03Standardized connection management via RUBE_MANAGE_CONNECTIONS

04Built-in support for pagination and bulk operations

0511 GitHub stars

06Multi-tool execution support for complex enrichment sequences

Use Cases

01Verifying prospect information before syncing to a CRM

02Automating lead enrichment by fetching professional contact data

03Building automated sales intelligence reports for outreach campaigns

Key Features

01Dynamic tool discovery for up-to-date Datagma API schemas

02Session-based workflow management for consistent data handling

03Standardized connection management via RUBE_MANAGE_CONNECTIONS

04Built-in support for pagination and bulk operations

0511 GitHub stars

06Multi-tool execution support for complex enrichment sequences

Use Cases

01Verifying prospect information before syncing to a CRM

02Automating lead enrichment by fetching professional contact data

03Building automated sales intelligence reports for outreach campaigns