contexer

What it does

Contexer serves as an engineering decision layer for AI coding agents, designed to preserve and organize critical engineering knowledge. Instead of allowing architectural decisions, constraints, conventions, and patterns to disappear within AI conversations, Contexer captures and structures this information into a shared organizational asset. This makes institutional knowledge accessible to teams and ensures consistency across AI-assisted development workflows.

How to set up

Contexer is available as an MCP (Model Context Protocol) server that can be integrated with Claude and other AI coding agents. Installation involves adding it to your MCP configuration and connecting it to your preferred coding environment such as Cursor or Claude Code. Detailed setup instructions are available on the GitHub repository.

Key features

• Captures and organizes architecture decisions and engineering patterns
• Preserves constraints and conventions for team consistency
• Integrates with Claude, Cursor, and other AI coding agents via MCP
• Transforms ephemeral AI conversations into persistent organizational knowledge
• Supports Python and works with multiple AI platforms including Gemini