Memwright
Embedded memory for AI agents with SQLite, pgvector, and Neo4j graph search.
What is Memwright?
Memwright is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to embedded memory for ai agents with sqlite, pgvector, and neo4j graph search.
Embedded memory for AI agents with SQLite, pgvector, and Neo4j graph search.
This server falls under the Knowledge & Memory category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- Embedded memory for AI agents with SQLite, pgvector, and Neo
Use Cases
Maintainer
Works with
Installation
PIP
pip install memwrightManual Installation
pip install memwrightConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
Frequently Asked Questions about Memwright
What is Memwright?
Memwright is a Model Context Protocol (MCP) server that embedded memory for ai agents with sqlite, pgvector, and neo4j graph search. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Memwright?
Install via pip with: pip install memwright. Then configure your AI client to connect to this MCP server.
Which AI clients work with Memwright?
Memwright works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Memwright free to use?
Yes, Memwright is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
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Browse More Knowledge & Memory MCP Servers
Explore all knowledge & memory servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.
Set Up Memwright in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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