IntelliJ Junie Configuration¶

This guide explains how to configure JetBrains Junie (the autonomous coding agent) to use the RIDDL MCP Server for AI-assisted domain modeling.

What is Junie?¶

Junie is JetBrains' autonomous AI coding agent that can understand your codebase, execute tasks, and make changes across multiple files. With the RIDDL MCP Server connected, Junie gains specialized capabilities for working with RIDDL domain models.

Prerequisites¶

IntelliJ IDEA 2024.2 or later with Junie support
Junie enabled in your JetBrains account
API key for the RIDDL MCP Server (contact support@ossuminc.com)

Configuration¶

Settings UI Method¶

Open Settings (Cmd+, or Ctrl+Alt+S)
Navigate to Tools > Junie
Find the MCP Servers or External Tools section
Click Add Server and enter:

Field	Value
Name	`riddl`
URL	`https://mcp.ossuminc.com/mcp/v1`
API Key Header	`X-API-KEY`
API Key	`your-api-key`

Configuration File Method¶

If your version requires file-based configuration:

Location: ~/.config/JetBrains/IntelliJIdea2024.x/junie/mcp-servers.json

{
  "mcpServers": {
    "riddl": {
      "url": "https://mcp.ossuminc.com/mcp/v1",
      "headers": {
        "X-API-KEY": "your-api-key"
      }
    }
  }
}

Server Coming Soon

The hosted MCP server at mcp.ossuminc.com will be available in early 2026. For now, use a local server for development. Replace your-api-key with your actual API key.

Using a Local Server¶

For development with a locally running server:

{
  "mcpServers": {
    "riddl": {
      "url": "http://localhost:8080/mcp/v1",
      "headers": {
        "X-API-KEY": "your-local-api-key"
      }
    }
  }
}

Restart IntelliJ¶

After configuration:

Close IntelliJ IDEA
Relaunch IntelliJ IDEA
Open Junie to verify RIDDL tools are available

Junie Capabilities with RIDDL¶

Autonomous Tasks¶

Junie can autonomously:

Validate all RIDDL files in your project
Fix validation errors across multiple files
Generate new entities, contexts, or domains
Refactor RIDDL structures
Add missing documentation

Example Autonomous Tasks¶

"Validate and fix my RIDDL model"¶

Junie will:

Scan all .riddl files in the project
Run validation on each file
Identify and fix resolvable errors
Report issues requiring human decision

"Create a complete order management context"¶

Junie will:

Understand your existing domain structure
Generate entities, commands, events, and handlers
Ensure proper references between definitions
Validate the generated code

"Make this model simulation-ready"¶

Junie will:

Run check-simulability on your model
Identify missing handlers and state definitions
Add placeholder implementations
Re-validate until simulation-ready

Usage Examples¶

Project-Wide Validation¶

Open Junie and ask:

Validate all RIDDL files in this project and create a report of any issues

Generate from Requirements¶

Create RIDDL definitions for a subscription management system with: - Monthly and annual plans - Automatic renewal - Cancellation handling - Usage tracking

Refactoring¶

Move the Payment entity from the Orders context to a new Payments context, updating all references

Documentation¶

Add brief descriptions to all entities and types that are missing documentation

Error Resolution¶

The validation shows 15 undefined reference errors. Fix them by adding the missing type definitions

Junie + RIDDL4IDEA¶

For the best experience, use both:

RIDDL4IDEA Plugin¶

Real-time syntax highlighting
Inline validation as you type
Clickable error navigation
Manual validation control

Junie with RIDDL MCP¶

Autonomous multi-file operations
Natural language task execution
Intelligent code generation
Batch error fixing

Workflow Example¶

Write code - RIDDL4IDEA shows instant feedback
Hit a complex issue - Ask Junie for help
Need new features - Describe to Junie in natural language
Review changes - Junie shows diffs before applying
Validate - Both tools confirm correctness

Advanced Usage¶

Custom Prompts¶

Create reusable prompts for common RIDDL tasks:

# .junie/prompts/validate-model.md

Validate all RIDDL files in the project using the MCP server.
For each error:
1. Explain what's wrong
2. Suggest a fix
3. Apply the fix if it's unambiguous
4. Ask for confirmation on ambiguous fixes

Integration with Tests¶

After generating RIDDL code, validate it and check if it would pass simulation. Report any issues that would prevent simulation.

Continuous Improvement¶

Review my RIDDL model and suggest improvements for: - Better naming conventions - Missing error handling - Incomplete handlers - Documentation gaps

Troubleshooting¶

Junie Not Available¶

Verify Junie is enabled in your JetBrains account
Check IntelliJ version supports Junie
Update to latest IntelliJ version

MCP Tools Not Working¶

Restart IntelliJ after configuration
Check Junie logs: View > Tool Windows > Junie > Logs
Verify network connectivity to MCP server

Tasks Timing Out¶

Large projects may need longer timeouts
Consider running validation on subsets of files
Check server response times

Unexpected Changes¶

Always review Junie's proposed changes before applying
Use version control to track and revert if needed
Start with smaller tasks to build confidence

Best Practices¶

Start small: Test Junie with simple RIDDL tasks first
Review diffs: Always review changes before applying
Use version control: Commit before running autonomous tasks
Provide context: Include relevant requirements in your prompts
Iterate: Break large tasks into smaller, verifiable steps

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