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memory

Local-first project memory for AI coding agents.

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build.protocol_tooling.mcp#ai#agents#ai-coding-agents#ai-coding-assistants#coding-agents#persistent-memory#project-memory#agent-memory#local-first#mcp

Install memory in your MCP client

memory is a Model Context Protocol server. Add it to your MCP client config once, restart, and the server's tools become available to your AI assistant. The same JSON snippet below works across all four major clients — only the config file path differs.

  1. Locate your client's MCP config file.
    • Cursor: ~/.cursor/mcp.json
    • Claude Desktop (macOS): ~/Library/Application Support/Claude/claude_desktop_config.json
    • Claude Desktop (Windows): %APPDATA%\Claude\claude_desktop_config.json
    • VS Code: Settings → Extensions → MCP
    • Windsurf: Settings → MCP Servers
  2. Add memory to the mcpServers map — paste the snippet below into your config file. If you already have other MCP servers, merge the entry into the existing mcpServers object.
  3. Restart your client so it picks up the new server.
  4. Verify — ask the assistant to list available tools; memory's tools should appear.
{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": [
        "-y",
        "@aictx/memory"
      ]
    }
  }
}

Install memory in Cursor

Open ~/.cursor/mcp.json in your editor, paste the snippet above into mcpServers, save, and restart Cursor. memory will show up in the assistant's tool list on next launch.

Install memory in Claude Desktop (macOS)

Open ~/Library/Application Support/Claude/claude_desktop_config.json in your editor, paste the snippet above into mcpServers, save, and restart Claude Desktop (macOS). memory will show up in the assistant's tool list on next launch.

Install memory in Claude Desktop (Windows)

Open %APPDATA%\Claude\claude_desktop_config.json in your editor, paste the snippet above into mcpServers, save, and restart Claude Desktop (Windows). memory will show up in the assistant's tool list on next launch.

Install memory in VS Code

Open Settings → Extensions → MCP in your editor, paste the snippet above into mcpServers, save, and restart VS Code. memory will show up in the assistant's tool list on next launch.

npm package: @aictx/memory

Transport

memory supports the following MCP transports. Most AI clients use stdio by default for locally-installed servers.

stdio

From the memory README

# Memory ![Memory is a local wiki for AI agents. Agents load repo context, keep it current, and you review changes.](site/public/assets/readme-value-header.png) <p align="center"> <a href="https://memory.aictx.dev"><img alt="Website" src="https://img.shields.io/badge/website-memory.aictx.dev-111214?style=for-the-badge"></a> <a href="https://docs.aictx.dev"><img alt="Docs" src="https://img.shields.io/badge/docs-read-111214?style=for-the-badge"></a> <a href="https://demo.aictx.dev/?token=demo"><img alt="Live demo" src="https://img.shields.io/badge/demo-viewer-111214?style=for-the-badge"></a> </p> <p align="center"> <a href="https://github.com/aictx/memory/actions/workflows/ci.yml"><img alt="CI" src="https://github.com/aictx/memory/actions/workflows/ci.yml/badge.svg"></a> <a href

Other Model Context Protocol servers in the same space as memory. Each one adds different capabilities to your AI assistant — pick based on the data sources or workflows you need.

Browse the full MCP server directory or use Stork's one-line install to let your agent pick the right server automatically.