Built by the Fctr Identity team • Not affiliated with Okta

TAKO MCP Server for Okta (beta v0.1)

⚡ Powered by Anthropic's Code Execution with MCP Architecture

Production-ready MCP server implementing Anthropic's Code Execution with MCP pattern with dual-mode operation, context-engineering, enhanced security sandbox, and enterprise-grade features.

Overview

A production-ready MCP server for Okta administration with dual-mode operation. Successor to okta-mcp-server.

This server enables AI assistants to query Okta resources using the Model Context Protocol. It is designed for IAM engineers, security teams, and Okta administrators who want to give their AI tools safe, controlled access to their Okta environment.

Key Features:

• 🔄 Dual-Mode Operation - Standard MCP server mode or autonomous agent mode
• 🌐 Flexible Transports - STDIO for desktop clients, HTTP for remote deployments
• 🔑 Okta Tokens - API Token (simple) or OAuth2 with Private Key JWT (production)
• 📊 CSV Export - Save query results to files for reporting
• 🔒 Secure Execution - AST-based sandbox with whitelisted operations
• ✅ MCP Compliant - Elicitation, Progress notifications, logging, and tool annotations

📋 Table of Contents

• Core Concepts
• Quick Start
• Configuration
  • Okta Authentication
• MCP Client Setup
• Available Tools
• Security
• Rate Limits
• Get Help
• License

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🧠 Core Concepts

Before installing, it's helpful to understand the two key configuration choices: Mode and Transport.

1. Operating Modes

Controls how the AI interacts with the server. Set via ENABLE_AGENT_MODE environment variable.

Feature	Basic MCP Mode (false)	Agent Mode (true)
Context Size	Higher - all tools loaded upfront	Lower - progressive discovery
Token Cost	Higher initial cost	Lower initial cost
Use Case	MCP gateways, tool composition, granular control	Autonomous AI workflows
Architecture	Standard MCP tool exposure	Meta-tool discovery pattern
Data Fetching	Sample data (3 results) + endpoint metadata	Full result sets via code execution
Available Tools	read_system_instructions, get_code_generation_prompt, execute_code, okta_* tools	get_available_operations, get_operation_details, get_code_generation_prompt, execute_code

Basic MCP ServerMode (Default)

Tools exposed directly to the LLM. The AI calls read_system_instructions() first, then uses okta_* tools for sample data and execute_code() for full results.

Can be used for:

Category	Supported Platforms
Desktop Clients	Claude Desktop, Cursor, Zed, VS Code (Windsurf)
Enterprise Gateways	Obot.ai, Smithery, Lasso Security
Agent Frameworks	LangGraph, LlamaIndex, Goose

Agent Mode

AI discovers APIs dynamically via get_available_operations() and get_operation_details(), then generates code for execution. This mode is ideal for complex, multi-step queries where the agent explores the API surface as needed.

2. Transports

Controls how clients connect to the server.

Transport	Description	Best For
STDIO (Default)	Communicates via standard input/output pipes.	Local desktop apps (Claude, Cursor, VS Code).
HTTP (SSE)	Exposes a web server endpoint (/mcp).	Remote deployments, Docker, Web-based agents.

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🚀 Quick Start

Choose the installation method that fits your workflow.

Option A: Docker (Recommended)

The fastest way to get started without managing Python dependencies.

# 1. Clone the repository
git clone https://github.com/fctr-id/fctr-okta-mcp-server.git
cd fctr-okta-mcp-server

# 2. Create directories for persistent data
mkdir -p logs okta_results  # Windows: New-Item -ItemType Directory -Path logs, okta_results -Force

# 3. Create a .env file (see Configuration section for all options)
cp .env.sample .env
# Edit .env with your Okta credentials

# 4. Build with Docker
docker build --target stdio -t tako-mcp-server:stdio .  # STDIO mode
docker build --target http -t tako-mcp-server:http .    # HT

{"mcpServers": {"tako-okta": {"command": "docker", "args": ["run", "-i", "--rm", "-e", "OKTA_ORG_URL", "-e", "OKTA_API_TOKEN", "tako-mcp-server:stdio"]}}}