What is 'Cross-Agent Workspace Sync'?

This feature automatically detects and migrates your MCP server configurations, rules, and skills across all supported AI coding agents, ensuring your setup is consistent everywhere.

How does Memorix help share knowledge across agents?

It stores project knowledge in an MCP-compatible Knowledge Graph and offers token-efficient 3-Layer Progressive Disclosure search, capturing decisions, errors, and learnings automatically.

Does Memorix store my data in the cloud?

No, Memorix operates as a lightweight *local* MCP server. It can optionally use local `fastembed` for vector search, ensuring your code memories and configurations remain private on your machine.

Memorix is a universal memory layer and workspace synchronization tool for AI coding agents, enabling seamless knowledge sharing and consistent environments across multiple platforms.

Which AI coding agents does Memorix support?

Memorix supports popular agents like Windsurf, Cursor, Claude Code, Codex, and VS Code Copilot, ensuring broad compatibility via the Model Context Protocol (MCP).

Memorix: Cross-Agent Memory & Workspace Sync for AI Coders

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Memorix is a lightweight local Model Context Protocol (MCP) server that establishes a universal memory layer for AI coding agents. It solves the fragmentation problem by storing and indexing project knowledge—including architectural decisions, bug fixes, and code style preferences—making it accessible to any MCP-supporting agent. Memorix automatically synchronizes MCP configurations, rules, skills, and workflows across diverse AI coding environments such as Windsurf, Cursor, Claude Code, Codex, and VS Code Copilot, ensuring knowledge continuity and a unified workspace experience.

Características Principales

Cross-Agent Workspace Sync: Automatically detects and migrates MCP configs, rules, and skills across 5 popular AI coding agents.
Auto-Memory Hooks: Automatically captures decisions, errors, gotchas, and learnings from agent interactions with cooldown and noise filtering.
Hybrid Search: Combines full-text (BM25) and optional vector (semantic) search capabilities via Orama for intelligent retrieval.
Knowledge Graph: Implements an Entity-Relation model compatible with official MCP Memory Servers for structured knowledge management.
3-Layer Progressive Disclosure: Offers token-efficient search results through compact indexes (L1), chronological context (L2), and full details on demand (L3).
1 GitHub stars

Casos de Uso

Maintaining project context and knowledge continuity across various AI coding agents throughout the development lifecycle.
Synchronizing development rules, custom skills, and MCP configurations between different AI-powered IDEs and coding assistants.
Automating the capture and indexing of coding decisions, errors, and learnings to ensure AI agents have access to all relevant historical information.

Acerca de

Características Principales

Cross-Agent Workspace Sync: Automatically detects and migrates MCP configs, rules, and skills across 5 popular AI coding agents.
Auto-Memory Hooks: Automatically captures decisions, errors, gotchas, and learnings from agent interactions with cooldown and noise filtering.
Hybrid Search: Combines full-text (BM25) and optional vector (semantic) search capabilities via Orama for intelligent retrieval.
Knowledge Graph: Implements an Entity-Relation model compatible with official MCP Memory Servers for structured knowledge management.
3-Layer Progressive Disclosure: Offers token-efficient search results through compact indexes (L1), chronological context (L2), and full details on demand (L3).
1 GitHub stars

Casos de Uso

Maintaining project context and knowledge continuity across various AI coding agents throughout the development lifecycle.
Synchronizing development rules, custom skills, and MCP configurations between different AI-powered IDEs and coding assistants.
Automating the capture and indexing of coding decisions, errors, and learnings to ensure AI agents have access to all relevant historical information.