# Memwyre

## Docs

- [Overview](https://docs.memwyre.tech/index.md): Learn about Memwyre — the universal persistent memory layer that connects developer IDEs, browser tools, and autonomous AI agents through a unified entity graph.
- [Use Cases](https://docs.memwyre.tech/use-cases.md): Explore core use cases for Memwyre, including codebase synchronization, personalized AI memory, and team workflows.
- [Self-Hosting](https://docs.memwyre.tech/self-hosting.md): Learn how to host Memwyre locally or on your own private cloud using Docker Compose, PostgreSQL, and pgvector.
- [Universal MCP Server Guide](https://docs.memwyre.tech/integrations/mcp-server.md): Universal guide to connecting Memwyre to Model Context Protocol (MCP) clients like Claude Desktop, Cursor, and VS Code.
- [CLI Auto-Installer Guide](https://docs.memwyre.tech/integrations/cli-installer.md): Step-by-step instructions for running the Memwyre CLI installer to configure local MCP servers and developer hooks.
- [Claude Desktop MCP Integration](https://docs.memwyre.tech/integrations/mcp-server/claude.md): Configure Memwyre as a local MCP server for Claude Desktop to maintain a persistent chat memory layer.
- [Cursor AI IDE MCP Integration](https://docs.memwyre.tech/integrations/mcp-server/cursor.md): Configure Memwyre inside Cursor AI IDE to maintain persistent codebase memories across editing sessions.
- [VS Code MCP Agent Caching](https://docs.memwyre.tech/integrations/mcp-server/vscode.md)
- [Openclaw](https://docs.memwyre.tech/integrations/plugins/openclaw.md): Install the Memwyre plugin for OpenClaw autonomous agents to query and persist memory graphs across agent runs.
- [Claude Code](https://docs.memwyre.tech/integrations/plugins/claude.md): Integrate Memwyre lifecycle hooks into Claude Code CLI to automatically save and retrieve terminal session memory.
- [How Memwyre Works ](https://docs.memwyre.tech/how-it-works.md): Understand the architectural concepts of Memwyre, including memory decay curves, graphs, profiles, and routing.
- [RAG vs. Persistent AI Memory](https://docs.memwyre.tech/rag-vs-memory.md): Compare traditional RAG retrieval with Memwyre's persistent memory layer to see how entity profiling improves context relevance.
- [Latency & Performance Benchmarks](https://docs.memwyre.tech/benchmarks.md): Read the performance and latency benchmark report comparing Memwyre's retrieval with Mem0, Zep, and Supermemory.
- [Security & Data Privacy](https://docs.memwyre.tech/security.md): Read about Memwyre security practices, including private memory vaults, data encryption, and local offline deployment.