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MCP server

DataMaker ships a Model Context Protocol server that exposes the platform’s full surface as tools. Configure it in your AI coding agent (Claude, Cursor, Copilot, or any other MCP-aware client), and the agent can generate, fetch, push, mask, and run scenarios without leaving the editor.

What you get

  • A full set of tools covering templates, connections, generation, scenarios, plans, and SAP OData.
  • Real auth: the MCP server runs against your real DataMaker workspace using your real API key. No sandboxes.
  • Streaming: long-running tools (like generate_from_id) stream their output back to the agent so it can react incrementally.
  • Workspace-aware: the server knows your project ID, so get_templates returns your templates, not a public catalogue.

Install

The MCP server runs as a stdio process. Install it once with pipx:

Terminal window
pipx install datamaker-mcp

Or npx (Node version):

Terminal window
npx -y datamaker-mcp --version

Configure your agent

Each agent has its own config file. Three of the common ones below.

Claude Desktop / Claude Code

Add to your config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS, or in Claude Code via claude mcp add):

{
  "mcpServers": {
    "datamaker": {
      "command": "datamaker-mcp",
      "env": {
        "DM_API_KEY":     "${DM_API_KEY}",
        "DM_PROJECT_ID":  "proj_xxx"
      }
    }
  }
}

Cursor

~/.cursor/mcp.json:

{
  "mcpServers": {
    "datamaker": {
      "command": "datamaker-mcp",
      "env": {
        "DM_API_KEY":     "your-key",
        "DM_PROJECT_ID":  "proj_xxx"
      }
    }
  }
}

GitHub Copilot

In VS Code with the MCP preview enabled:

settings.json
{
  "github.copilot.mcp.servers": {
    "datamaker": {
      "command": "datamaker-mcp",
      "env": { "DM_API_KEY": "your-key" }
    }
  }
}

For other clients, see Clients setup.

What it looks like

Once configured, the agent has access to tools like get_templates, generate_from_id, create_template_from_csv, list_integrations, and the Plan tools, plus the SAP/OData and code-execution tools from the connected servers. You ask in plain English; the agent picks the tools. See the full tool catalogue.

A real example, abridged:

you:    Build a customer template from sample.csv and generate 200 rows.


agent:  Creating the template…
        [calls create_template_from_csv with the file URL]
        Created "Customer" with 6 fields. Generating…
        [calls generate_from_id with count=200]
        ✓ 200 rows generated.

Pages

Source

datamaker-mcp is open source: github.com/automators-com/datamaker-mcp. File issues and PRs there.