Skene, developed by Skenetechnologies, is a free MCP server tool designed for Product-Led Growth analysis. Built primarily with Go and Python, it helps teams understand user journeys by analyzing codebases and SQL schemas. Skene identifies product lifecycle stages, key milestones, and supporting evidence directly within technical assets. It offers both an interactive terminal UI and a Python CLI for various operational needs. This toolkit integrates with several AI clients, enhancing its analytical capabilities for growth feature discovery and plan generation.

What does Skene connect to?

Skene functions as a Product-Led Growth analysis toolkit, connecting directly to codebases and SQL schemas. Its purpose is to analyze these technical foundations to map out a product's user journey. By examining the underlying code and database structures, Skene identifies critical lifecycle stages, key milestones, and the specific evidence supporting these within the application's technical implementation. This deep connection allows for data-driven insights into product usage and growth opportunities.

Core features and tools

Skene provides several key functionalities for growth analysis. These include Tech stack detection, which identifies the technologies used in a project. It also offers Growth feature discovery to pinpoint features driving user engagement, and Growth plan generation to suggest strategies for product evolution. Furthermore, Skene can create Implementation prompts to guide development efforts and features an Interactive chat for user interaction. While the exact callable MCP tool names are not explicitly detailed, these capabilities form its analytical core.

Who is it for?

Skene is for product teams, developers, and growth strategists seeking to understand user behavior and product adoption directly from their technical assets. It helps identify how code and database structures reflect user journeys and growth opportunities. Teams needing to map lifecycle stages and milestones within their existing codebase will find it valuable. This tool supports data-driven decision-making for product evolution. Skip this if your analysis needs do not involve direct code or SQL schema examination.

How to get started

The server authenticates using an API key passed as an environment variable, providing a direct method for securing access. For local audits, no credentials are required, simplifying initial exploration and development within a controlled environment. However, when connecting remotely, the SKENE_API_KEY environment variable must be configured, specifically for communication over the Streamable HTTP transport protocol, ensuring secure and authorized data exchange.

Use cases

• Analyzing a new codebase to quickly understand its tech stack and identify existing or potential growth features, aligning with user engagement patterns.
• Mapping user journeys by examining SQL schemas and application code to pinpoint distinct product lifecycle stages and critical user milestones.
• Generating implementation prompts for development teams, based on identified growth opportunities, feature gaps, and specific areas for product improvement.

Skene offers a unique approach to Product-Led Growth analysis by directly interpreting codebases and SQL schemas. Its integration with multiple AI clients, including Claude and OpenAI, enhances its ability to detect tech stacks, discover growth features, and generate actionable plans. The tool supports both local analysis without credentials and remote access via API keys. Try generating a growth plan for an existing product by analyzing its codebase.