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. For more information, see Job Management in the Control-M Automation API documentation.

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.

Control-M MCP Server is a Preview feature. Preview features enable you to provide early feedback on new ideas. You can raise Support cases for Preview features at Impact Level 3 and 4. Preview feature functionality might be modified in the future. BMC recommends that you utilize this feature in non-production environments.

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 you have Control-M Automation API 9.0.22.125 installed on Control-M/EM, as described in Control-M Automation API Installation. If you have a distributed environment, verify that the same version is installed on each Control-M/EM server.

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

  • For the best Control-M MCP Server user experience, BMC recommends that you use Java 25. Ensure that you have an external Java installation of this version. For more information, see External Java Management.

Begin

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

    If you configured Control-M MCP Server configured in automation-api.properties, it overrides the setting configured in the Control-M/EM General Parameters. BMC recommends that you remove the mcp.server.enabled=true parameter in the automation-api.properties file.

  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://emdomain:port/automation-api/mcp/stream",
           "--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://emdomain:port/automation-api/mcp/stream",
        "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://emdomain:port/automation-api/mcp/stream",
       "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 in one of the following formats:

  • Streamable HTTP: https://<Control-M/EM domain:port>/automation-api/mcp/stream

  • Stateless HTTP: https://<Control-M/EM domain:port>/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.