In Memoria

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In Memoria solves the common problem of session amnesia in AI coding assistants, which currently force developers to re-explain their codebase's architecture and patterns in every new conversation. It builds a persistent intelligence infrastructure that enables AI tools to learn and remember your specific coding style, architectural choices, and project organization through the Model Context Protocol, offering highly context-aware and personalized suggestions that evolve with your workflow.

Características Principales

• Provides persistent memory and pattern learning for AI coding assistants.
• Offers native AST parsing for 12 programming languages including TypeScript, Python, and Rust.
• Learns naming patterns, architectural choices, code structure preferences, and project organization.
• Exposes 17 specialized MCP tools for comprehensive codebase analysis and intelligence.
• Ensures high-performance analysis with smart file filtering, incremental updates, and timeout protection.
• 40 GitHub stars

Casos de Uso

• Enabling AI assistants to provide context-aware coding suggestions aligned with a developer's personal style and project patterns.
• Streamlining the onboarding of new development team members by sharing pre-learned codebase intelligence.
• Ensuring consistent architectural decisions and coding styles across a team through shared pattern recognition.