Okta + MCP: AI-Powered SOAR Workflows for Identity Management

The Okta MCP Server (GitHub) lets you access your Okta environment through the Model Context Protocol (MCP), enabling AI assistants to orchestrate seamless workflows across multiple systems. By integrating with other MCP servers for services like Google Drive, Slack, and GitHub, it creates a powerful ecosystem where complex cross-platform operations can be executed through natural language commands.

Executive Summary

The Okta MCP Server transforms how AI assistants interact with your Okta environment by providing a standardized protocol layer between AI models and Okta’s APIs. This integration enables natural language control of identity operations, real-time data access, and multi-system workflows—all while maintaining enterprise-grade security controls.

Current capabilities focus on read-only operations, with rapid expansion planned for additional entities and operations in upcoming releases. Please make sure to check the GitHub repo often for new tools

What is the Model Context Protocol (MCP)?

MCP enables AI assistants to interact with your Okta environment in real-time through a standardized interface that allows AI models to discover and use available operations while maintaining security boundaries.

Think of MCP as the “USB-C of AI integration” – creating a universal way for AI models to interact with different services without custom integration for each one. This approach lets developers build tools once that work across multiple AI assistants.

For more technical details on MCP, visit the protocol documentation.

Practical Use Cases: The Power of Integrated MCP Workflows

The true magic of MCP servers emerges when multiple tools work together through your AI assistant to create seamless workflows:

Note: These workflows were possible with custom scripts, but the beauty of MCP is that you can build these now with natural language prompts.

• Export locked Okta users to Google Drive – “Find all locked users in our Okta tenant, and create a spreadsheet in our IT Operations folder on Google Drive with their names, email addresses, and last login dates.”

• Secure compromised accounts and document the incident – “For all users who failed MFA more than 5 times today, suspend their Okta accounts, add them to the ‘Security Review’ group, and create an incident report in our security Slack channel with the details.”

How It Works: Behind the scenes, the LLM orchestrates these workflows by gathering tools from all MCP servers, identifying which ones are needed, processing your query, and seamlessly passing data between MCP servers/tools using a standardized protocol.

Key Features and Security Considerations

Secure API Integration

The Okta MCP Server provides secure, real-time access to user details, group memberships, and application assignments while implementing least-privilege permissions, fine-grained controls, and robust input validation—with plans to add human approval workflows for sensitive operations.

Multiple AI Client Support

The Okta MCP Server supports various AI platforms through the standardized MCP protocol, including Claude Desktop, Microsoft Copilot Studio, Fast-agent, and any other MCP-compatible client.

Important: Security & Privacy Considerations

Before implementing the Okta MCP Server, understand how data flows through this architecture:

Data Privacy with AI Models

When using the Okta MCP Server:

• ⚠️ All Okta data returned by the tools WILL BE SENT to the AI model ⚠️
• This data remains in the model’s context for the duration of the conversation
• You must be comfortable with your data being processed according to your AI provider’s policies

Working Within Context Limitations

MCP is designed for lightweight workflows, not bulk data operations:

Recommendation: Limit requests to fewer than 100 entities per transaction.

❌ Not recommended:

• “Fetch all users from our Okta tenant and analyze their login patterns”
• “Find users who do not have Okta Verify enrolled as a factor”

✅ Effective:

• “Get the most recently created 20 users”
• “Find users who haven’t logged in for 90+ days, limit to first 50 results”

Transport Security Warning

The MCP Server offers two transport modes:

• STDIO (Standard I/O): The secure default option, recommended for most use cases
• SSE (Server-Sent Events over HTTP): Has significant security risks – DO NOT USE it without securing the HTTP endpoint

What’s Next: Roadmap and Future Plans

Key upcoming enhancements to the Okta MCP Server include:

• Expanded API Coverage: More Okta entities and write operations
• Human-in-the-Loop: Approval mechanisms for sensitive operations
• Multi-tenant Support: Managing multiple Okta environments from a single instance
• Integration with AI Agent: Combining real-time operations with historical analysis

Complementary Solutions and Available Ecosystem

Feature	AI Agent for Okta	Okta MCP Server
Data Source	Local SQLite database (synced periodically)	Live Okta API (real-time)
Query Speed	Fast (queries local database)	API-limited (queries live Okta)
Data Freshness	Point-in-time (from last sync)	Real-time (current Okta state)
Use Case	Data analysis, reporting, pattern recognition	Current state verification, real-time operations

The Okta MCP Server works with other MCP servers like Google Drive, GitHub, Jira, and Slack to create powerful cross-application workflows. Find available implementations at the MCP servers repository.

Conclusion

The Okta MCP Server represents a significant advancement in AI-powered identity management, enabling seamless integration between AI models and your identity infrastructure.

We encourage you to explore the project on GitHub (https://github.com/fctr-id/okta-mcp-server). For questions, reach out to support@fctr.io, or for contributing, reach out to dan@fctr.io.

Appendix: Technical Configuration

Sample Client Configuration

For MCP clients like Claude Desktop, add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "okta-mcp-server": {
      "command": "DIR/okta-mcp-server/venv/Scripts/python",
      "args": [
        "DIR/okta-mcp-server/main.py"
      ],
      "env": {
        "OKTA_CLIENT_ORGURL": "https://dev-1606.okta.com", 
        "OKTA_API_TOKEN": "OKTA_API_TOKEN"
      }
    }
  }
}

Make sure to replace:

• DIR with the absolute path to your directory
• OKTA_CLIENT_ORGURL with your okta org url
• OKTA_API_TOKEN with your actual Okta API token