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MTA Skills for AI Agents

Three complementary skills for Java application migration powered by Konveyor/MTA:

  1. mta-analyze - Analyze codebases for migration readiness using MTA CLI (kantra or mta-cli)
  2. mta-rules-gen - Generate custom migration rules using the Scribe MCP server
  3. mta-migration - Orchestrate end-to-end application migrations with planning and execution

Workflow

graph LR
    Start([Your App]) --> Analyze[📊 /mta-analyze<br/>Analyze & assess]
    Start --> Rules[⚙️ /mta-rules-gen<br/>Create custom rules]
    Start --> Migrate[🚀 /mta-migration<br/>Plan & execute]
    
    Analyze --> Report[HTML Report]
    Rules --> Ruleset[YAML Rules]
    Migrate --> Complete[Migrated App]
    
    style Analyze fill:#e1f5ff,stroke:#0288d1,stroke-width:2px
    style Rules fill:#fff4e1,stroke:#f57c00,stroke-width:2px
    style Migrate fill:#e1ffe1,stroke:#388e3c,stroke-width:2px
    style Report fill:#f5f5f5
    style Ruleset fill:#f5f5f5
    style Complete fill:#c8e6c9
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📖 Detailed Workflow (click to expand) 
graph TB
    Start([User Request]) --> Decision{What do you need?}
    
    Decision -->|Analyze only| Analyze[/mta-analyze/]
    Decision -->|Generate rules only| RulesGen[/mta-rules-gen/]
    Decision -->|Full migration| Migration[/mta-migration/]
    
    Analyze --> Kantra[Run MTA CLI<br/>kantra or mta-cli]
    Kantra --> CustomRules{Custom rules<br/>exist?}
    CustomRules -->|Yes| AnalyzeWithRules[Analyze with<br/>custom rules]
    CustomRules -->|No| AnalyzeDefault[Analyze with<br/>default rules]
    AnalyzeWithRules --> Report1[Generate<br/>HTML Report]
    AnalyzeDefault --> Report1
    Report1 --> End1([Analysis Complete])
    
    RulesGen --> Scribe[Connect to<br/>Scribe MCP]
    Scribe --> GenerateRules[Generate custom<br/>YAML rules]
    GenerateRules --> SaveRules[Save to<br/>ruleset/]
    SaveRules --> End2([Rules Ready])
    
    Migration --> Phase1[Phase 1:<br/>Analysis]
    Phase1 --> RunAnalyze[Use mta-analyze]
    RunAnalyze --> Phase2[Phase 2:<br/>Gap Detection]
    Phase2 --> Gaps{Missing<br/>rules?}
    Gaps -->|Yes| UseRulesGen[Use mta-rules-gen]
    Gaps -->|No| Phase3[Phase 3:<br/>Create Plan]
    UseRulesGen --> SaveToRuleset[Save to ruleset/]
    SaveToRuleset --> ReAnalyze[Re-run analysis<br/>with custom rules]
    ReAnalyze --> Phase3
    Phase3 --> CreatePlan[Generate<br/>MIGRATION_PLAN.md]
    CreatePlan --> UserApproval{User<br/>approves?}
    UserApproval -->|No| End3([Plan Review])
    UserApproval -->|Yes| Phase4[Phase 4:<br/>Execution]
    Phase4 --> GitBranch[Create git branch]
    GitBranch --> Execute[Execute phases:<br/>deps → code → config → tests]
    Execute --> Validate[Validate each phase]
    Validate --> End4([Migration Complete])
    
    style Analyze fill:#e1f5ff
    style RulesGen fill:#fff4e1
    style Migration fill:#e1ffe1
    style Kantra fill:#f0f0f0
    style Scribe fill:#f0f0f0
    style End1 fill:#c8e6c9
    style End2 fill:#c8e6c9
    style End3 fill:#fff9c4
    style End4 fill:#c8e6c9
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e.g Prompt

/mta-migration migrate this application to eap 8

Output

Installation

Local install (installs to .claude/skills/ in current directory):

npx @sshaaf/mta-skill

Global install (installs to ~/.claude/skills/ for all projects):

npx @sshaaf/mta-skill -g

** Development** during development you can run installer.js e.g. /home/user/mta-skill/installer.js. This should install the skill in local .claude directory.

cd current-project
/home/user/mta-skill/installer.js

The skill will be available to any AI agent that supports the .claude/skills/ directory structure.

Usage

MTA Analysis (/mta-analyze)

Analyze your codebase for migration readiness:

/mta-analyze analyze this codebase for migration to EAP 8

Or naturally:

Analyze this Java app for migration to Quarkus
Check if we can migrate to EAP 8
Run a cloud readiness assessment

The skill will:

  1. Check if kantra is installed
  2. Auto-detect custom migration rules
  3. Run the analysis with appropriate targets
  4. Generate a detailed HTML report
  5. Summarize key findings and migration effort

Rules Generation (/mta-rules-gen)

Generate custom migration rules using Scribe:

/mta-rules-gen create rules for Spring Boot 2 to 3 migration

Or naturally:

Generate rules to detect deprecated Spring Security configs
Create rules for WebLogic JMS to Jakarta JMS migration
I need rules to flag our internal deprecated APIs

The skill will:

  1. Connect to Scribe MCP server (http://localhost:8080/mcp/sse)
  2. Generate custom MTA rules based on your requirements
  3. Save rules as YAML files in migration-rules/
  4. Provide usage instructions for kantra --rules flag

Migration Orchestration (/mta-migration)

Orchestrate complete application migrations:

/mta-migration migrate this Spring Boot 2.7 app to 3.2

Or naturally:

Migrate this application from WebLogic to Quarkus
Upgrade this app from Java EE 7 to Jakarta EE 10
Modernize this application to Spring Boot 3

The skill will:

  1. Run MTA analysis on your codebase
  2. Identify gaps and generate custom rules if needed
  3. Create a comprehensive migration plan with phases
  4. Create a git branch for safe execution
  5. Execute the migration with validation at each step
  6. Provide rollback instructions if needed

Example Workflows

Workflow 1: Analysis-Only

# Step 1: Generate custom rules
You: Create migration rules for detecting Spring Boot 2.x security configs

Agent: [uses mta-rules-gen]
       Generated rules saved to: migration-rules/springboot2-security-rules.yaml
       
       Rules detect:
       • Deprecated WebSecurityConfigurerAdapter
       • Old authentication patterns
       • Changed property names
       
       Usage: kantra analyze --rules=./migration-rules ...

# Step 2: Analyze codebase with custom rules
You: Now analyze this codebase for Spring Boot 3 migration using those rules

Agent: [uses mta-analyze]
       Running kantra with custom rules...
       
       Migration Analysis Complete
       
       Key Findings:
       • Total Issues: 18 mandatory, 12 optional, 5 potential
       • Custom rules found: 8 security configuration issues
       • Estimated Effort: 52 story points
       
       📊 Full Report: /path/to/kantra-output-*/static-report/index.html

Workflow 2: Full Migration Orchestration

You: Migrate this Spring Boot 2.7 application to Spring Boot 3.2

Agent: [uses mta-migration]
       
       Phase 1: Analysis
       Running MTA analysis...
       Found 15 mandatory issues, 8 optional improvements
       
       Phase 2: Gap Analysis
       Identified missing rules for internal APIs
       Generating custom rules via Scribe MCP...
       Saved to: ruleset/custom-rules.yaml
       
       Phase 3: Migration Plan
       Created comprehensive plan: MIGRATION_PLAN.md
       
       Estimated effort: 42 story points
       • Dependency updates: 8 points
       • Code migrations: 28 points
       • Configuration: 6 points
       
       Would you like me to execute this migration?

You: Yes, proceed

Agent: Creating migration branch: migration/springboot27-to-32-20260519
       
       Executing Phase 1: Dependency Updates
       ✓ Updated parent POM to Spring Boot 3.2.x
       ✓ Build successful
       
       Executing Phase 2: Code Migrations
       ✓ Migrated javax.validation → jakarta.validation
       ✓ Updated SecurityConfig (removed WebSecurityConfigurerAdapter)
       ✓ Code compiles successfully
       
       Executing Phase 3: Tests
       ✓ All tests passing
       
       Migration Complete!
       Review changes: git diff main..migration/springboot27-to-32-20260519

Supported Migration Targets

  • JBoss EAP: eap6, eap7, eap8
  • Cloud Native: quarkus, cloud-readiness, camel
  • OpenJDK: openjdk11, openjdk17, openjdk21
  • Frameworks: spring-boot, jakarta-ee

Requirements

Both Skills

  • AI agent that supports skills (Claude Code, Cline, Roo-Code, etc.)
  • Java codebase to work with

MTA Analysis (mta-analyze)

  • MTA CLI (kantra or mta-cli) - See installation instructions below

Rules Generation (mta-rules-gen)

Migration Orchestration (mta-migration)

  • MTA CLI (kantra or mta-cli) - See installation instructions below
  • Scribe MCP Server (for custom rule generation) - https://github.com/sshaaf/scribe
  • Git repository - Codebase must be in a git repo for safe branching

Installing MTA CLI

The skills require the MTA CLI to be installed. You can use either kantra or mta-cli.

Option 1: Installing mta-cli (Recommended for ~/.kantra setup)

  1. Download the latest release from https://github.com/konveyor/kantra/releases
  2. Extract the downloaded archive: 
    tar -xzf kantra-<version>-<os>-<arch>.tar.gz
  3. Rename the extracted directory to mta-cli: 
    mv kantra-<version> mta-cli
  4. Create the .kantra directory in your home folder: 
    mkdir -p ~/.kantra
  5. Move the entire mta-cli directory into ~/.kantra/: 
    mv mta-cli ~/.kantra/
  6. Add to your PATH by adding this line to ~/.bashrc, ~/.zshrc, or ~/.bash_profile: 
    export PATH=$PATH:~/.kantra/mta-cli/bin
  7. Reload your shell configuration: 
    source ~/.bashrc  # or ~/.zshrc
  8. Verify installation: 
    mta-cli version

Option 2: Installing kantra (Simpler PATH setup)

  1. Download the latest release from https://github.com/konveyor/kantra/releases
  2. Extract the archive
  3. Add the kantra executable to a directory in your PATH (e.g., /usr/local/bin or ~/bin)
  4. Verify installation: 
    kantra version

Testing Your Installation

Once installed, test with a simple analysis. Important: You must run the command from the parent directory of your application, not from inside the application directory.

# Navigate to the parent directory of your application
cd /path/to/parent-directory

# Using mta-cli (analyze the app-directory subdirectory)
mta-cli analyze --output output --input <app-directory-name> --target quarkus --overwrite

# Using kantra (analyze the app-directory subdirectory)
kantra analyze --output output --input <app-directory-name> --target quarkus --overwrite

Example:

# If your app is at: /home/user/projects/my-app
# Navigate to:      /home/user/projects
cd /home/user/projects

# Then run:
mta-cli analyze --output output --input my-app --target quarkus --overwrite

Note: The --input cannot be . (current directory). You'll get an error: input path cannot be the current directory

The analysis report will be generated at output/static-report/index.html.

What It Does

MTA Analysis Skill

Automates the complete MTA CLI (kantra/mta-cli) analysis workflow:

  • Detects migration targets from natural language requests
  • Auto-discovers and offers to use custom rule sets
  • Creates timestamped output directories for tracking progress
  • Parses and summarizes analysis results with key metrics
  • Generates detailed HTML reports for in-depth review
  • Suggests next steps based on findings

Rules Generation Skill

Enables custom migration rule creation:

  • Uses Scribe MCP server for intelligent rule generation
  • Creates properly formatted MTA/Konveyor YAML rulesets
  • Generates rules for specific migration scenarios
  • Includes effort estimates and severity levels
  • Provides transformation hints and documentation links
  • Saves rules in reusable format for kantra --rules flag

Migration Orchestration Skill

Automates the complete migration lifecycle:

  • Combines MTA analysis with custom rule generation
  • Creates comprehensive migration plans with phases
  • Manages git branches for safe execution
  • Validates each phase (build, tests, startup)
  • Handles dependency updates, code changes, and configuration
  • Provides rollback instructions if migration fails
  • Commits changes incrementally for easy review

Compatible AI Agents

This skill works with any agent system that supports the skill format:

  • Claude Code (CLI, desktop, web)
  • Cline (VS Code extension)
  • Roo-Code (VS Code extension)
  • Continue (IDE extension)
  • Other skill-compatible AI agents

About

MTA skills for AI agents - Analyze codebases, generate custom migration rules, and orchestrate end-to-end migrations using Konveyor/MTA tools

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