Control-M MCP Server

Control-M MCP Server is a standards-based interface that enables AI agents and AI assistants to securely interact with Control-M workflows and automation services. It is built on the Model Context Protocol (MCP) and allows AI systems to dynamically discover Control-M capabilities and execute actions, such as trigger jobs, check workflow status, and investigate failures, as described in Job Management.

Control-M MCP Server lets you utilize your own corporate AI tools and models. You can connect the Control-M MCP Server to a central tool registry or MCP gateway, together with other MCP servers. This allows you to combine different tools into a single solution. For example, you can create a single AI prompt that uses multiple MCP servers. The AI agent queries and operates the different tools to support specific business requirements and automate workflows.

Control-M MCP Server supports elicitation, which prompts the user to confirm an action before it is executed. If you want to generate a confirmation request before you perform a Control-M action, your AI assistant must also support elicitation. Authorization to perform actions is defined in the User and Role Authorizations.

Control-M MCP Server can connect to a maximum of five AI assistants in parallel and support up to 60 requests per minute.

Control-M MCP Server does not run Forecast jobs.

Connecting AI Assistants to Control-M MCP Server

This procedure describes how to connect third-party AI assistants to Control-M MCP Server.

Before You Begin

• Verify that your AI assistant supports elicitation if you want to generate a confirmation request before you perform an action.

Begin

1. Enable Control-M MCP Server in Control-M Automation API, as described in config systemsettings:mcp::enable.

2. On your third-party AI assistant, add Control-M MCP Server with the settings, as described in Control-M MCP Server Settings.

   The configuration process to add an MCP server varies according to the AI assistant vendor.

   This generates a JSON file with the configured settings on your AI assistant.

   • Claude Desktop

   • Visual Studio

   • Cursor

   The following JSON is an example of the Control-M MCP Server configuration with an API token in Claude Desktop:

   Copy

   "controlm": {
      "command": "C:\\PROGRA~1\\nodejs\\npx.cmd",
      "args": [
         "-y", "mcp-remote",
          "https://<tenant-name>-aapi.<zone>.controlm.com:port/automation-api/mcp/message",
          "--header" {
             "x-api-key": "${env:CTM_API_TOKEN}"
             "Annotation-Subject": "Control-M MCP Sever Demo",
             "Annotation-Description": "This is a test message from Control-M MCP Server"
           }
         ]
   }

   If you copy the example for Claude Desktop, verify the following:

   • Node.js is installed on you AI assistant.

   • The command parameter value must not contain spaces. For example: C:\\Program Files\\nodjs\\npmx.cmd must be C:\\PROGRA~1\\nodejs\\npx.cmd

   The following JSON is an example of the Control-M MCP Server configuration with an API token in Visual Studio code:

   Copy

   "controlm": {
       "url": "https://<tenant-name>-aapi.<zone>.controlm.com:port/automation-api/mcp/message",
       "type": "http",
       "headers": {
          "x-api-key": "${env:CTM_API_TOKEN}"
          "Annotation-Subject": "Control-M MCP Sever Demo",
          "Annotation-Description": "This is a test message from Control-M MCP Server"
        }
   }

   The following JSON is an example of the Control-M MCP Server configuration with an API token in Cursor with stateless HTTP:

   Copy

   "controlm": {
      "url": "https://<tenant-name>-aapi.<zone>.controlm.com:port/automation-api/mcp/message",
      "type": "http",
      "headers": {
         "Content-Type": "application/json",
         "Accept": "application/json, text/event-stream",
         "x-api-key": "${env:CTM_API_TOKEN}",
         "Annotation-Subject": "Control-M MCP Sever Demo",
         "Annotation-Description": "This is a test message from Control-M MCP Server"
      }
   }

   If you utilize stateless HTTP in Cursor, you must add the following parameters in the headers:

   "Content-Type": "application/json"

   "Accept": "application/json"

3. Verify in the AI assistant that Control-M MCP Server is connected. A list of MCP tools appears when it is connected.

4. Type your prompt in the AI assistant. For prompt examples, see Control-M MCP Server Prompt Examples

Control-M MCP Server Settings

The following table describes the Control-M MCP Server settings.

Parameter	Description
url	Defines the URL of the Control-M MCP Server that you want to connect to the AI assistant with a stateless HTTP connection in the following format: https://<tenant-name>-aapi.<zone>.controlm.com/automation-api/mcp/message
type	Determines the server type, which must be a remote HTTP server that implements the MCP protocol. Valid Value: HTTP
headers > x-api-key	Defines an API token to grant access permissions to specific roles for a period that you can pre-define. You can create an API token with the authentication token::create API call or in Control-M Web, as described in Creating an API Token. You must include this API token in the HTTPS header of subsequent API calls in the following format: x-api-key: ${env:CTM_API_TOKEN} x-api-key can accept an API token. However, BMC recommends that you utilize the credential manager supported by your organization to ensure security.
headers> Annotation-Subject	(Optional) Defines the subject of the annotation that you want to add. You must add this parameter if annotations are enabled, as described in Annotation Input.
headers> Annotation-Description	(Optional) Defines the free-text annotation that you want to add. You must add this parameter if annotations are enabled, as described in Annotation Input.

Control-M MCP Server Prompt Examples

The following table describes various types of prompt examples.

Prompt Type	Examples
Job status	What is the current status of the "Daily_Billing_Report" job? Show me all jobs that failed in the last 2 hours. Are there any jobs currently running in the PROD environment? Which jobs ended not-OK today?
Logs and output	Show me the log for the last run of the "ETL_Load_Customers" job. What was the output of "File_Transfer_EU" job that ran this morning? Why did the "Archive_Orders" job fail? Show me the relevant log lines.
Job actions	Rerun the "Daily_Billing_Report" job. Hold the "Nightly_Backup" job until further notice. Release the "ETL_Load_Customers" job so it can run. Set the "Archive_Orders" job to OK.