Mainframe Assessment Tool MCP server

This page describes how to set up and interact with Mainframe Assessment Tool assessments by using MCP clients such as Gemini CLI or AI agents through the Model Context Protocol (MCP). You can use natural language prompts to get insights into your mainframe assessments. With the MCP server, you can use AI agents to perform discovery and analysis operations on your Mainframe Assessment Tool assessments. For example, you can do the following:

• List and view existing assessments.
• Explore business domains discovered in your assessments.
• Search and filter assets based on different criteria.
• Retrieve asset specifications, including dependencies and complexity metrics.

For more information on MCP, see What is the Model Context Protocol (MCP)? .

Before you begin

Make sure that you are familiar with Mainframe Assessment Tool, and that you have already used it to run an assessment.

Enable the MCP server

To enable the MCP server on your Mainframe Assessment Tool VM instance, add the MAT_ENABLE_MCP metadata key and set its value to true by running the following gcloud command:

 gcloud compute instances add-metadata INSTANCE_NAME 
\
    --metadata=MAT_ENABLE_MCP=true \
    --zone= ZONE 
 

Replace the following:

• INSTANCE_NAME : the name of your VM instance.
• ZONE : the zone where your VM instance is located.

If you set the metadata key on a running VM, you must restart the VM for the changes to take effect.

Connect to the MCP server

You can connect to the MCP server using standard AI agents that supports MCP connections over Streamable HTTP.

The MCP server is located under the /mcp/ route of the same port used to access the Mainframe Assessment Tool UI, see Access Mainframe Assessment Tool VM from your computer .

Configuration examples

The following sections provide examples of how to configure different AI agents to connect to the MCP server.

Replace LOCAL_PORT : with the local port used for accessing the Mainframe Assessment Tool UI.

Gemini CLI

To use Gemini CLI , configure the MCP server in the Gemini CLI settings file as follows:

  { 
  
 "mcpServers" 
 : 
  
 { 
  
 "mainframe-assessment-tool" 
 : 
  
 { 
  
 "httpUrl" 
 : 
  
 "http://localhost: LOCAL_PORT 
/mcp/" 
  
 } 
  
 } 
 } 
 

For more information, see Configure the MCP server in settings.json .

Antigravity IDE

To use Antigravity IDE , configure custom MCP server in mcp_config.json as follows:

  { 
  
 "mcpServers" 
 : 
  
 { 
  
 "mainframe-assessment-tool" 
 : 
  
 { 
  
 "serverUrl" 
 : 
  
 "http://localhost: LOCAL_PORT 
/mcp/" 
  
 } 
  
 } 
 } 
 

MCP server tools

The Mainframe Assessment Tool MCP server provides tools that enable AI agents to retrieve data from your assessments.

ListAssessments

Lists all the assessments that exist on the Mainframe Assessment Tool instance. Each assessment includes its name, ID, description, and timestamps.

ListDomains

Lists the domains for a given Mainframe Assessment Tool assessment ID. Each domain includes its name, description, and ID.

Arguments

ListAssets

Lists the assets for a given Mainframe Assessment Tool assessment ID. Each asset includes its ID, name, path, type, and assigned domain IDs.

Arguments

FetchDomain

Fetches the domain details for a given domain ID and Mainframe Assessment Tool assessment ID. Domain details include ID, name, description, and summary.

Arguments

FetchAsset

Fetches the specification summary for an asset for a given Mainframe Assessment Tool assessment ID. The asset specification includes its ID, name, usage, description, ETL graph, and BMS maps.

Arguments

FetchAssetsCyclomaticComplexity

Fetches the cyclomatic complexity scores for a list of assets for a given Mainframe Assessment Tool assessment ID.

Arguments

ListBusinessRulesExtractionJobs

Lists the Business Rules Jobs for a given Mainframe Assessment Tool assessment ID. The returned list includes each job's ID, name, status, focus prompt and more.

Arguments

ListBusinessRules

Lists the Business Rules that were extracted by a given business rules extraction job ID and Mainframe Assessment Tool assessment ID. To handle a large amount of rules, this action supports pagination.

Arguments

Usage Examples

The following are examples of natural language prompts that an AI agent can answer by using the MCP server tools to retrieve and process assessment data:

• Scenario: Find complex programs in an assessment.
• User prompt: "List the 10 most complex COBOL programs in the assessment called AssessmentName ."
  
  
• Scenario: Find and filter assets that belong to a business domain.
• User prompt: "List all the JCL jobs related to the DomainName domain under the assessment called AssessmentName ."
  
  
• Scenario: Get asset dependencies from an assessment.
• User prompt: "What are the dependencies of the JCL job JCLJobName in the assessment called AssessmentName ?"
  
  
• Scenario: Find the extracted business rules from the certain job.
• User prompt: "List all business rules extracted by BusinessRuleJobName in the assessment called AssessmentName ?"