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mcp-memory

🔥🖥️ MCP Memory is a MCP Server that gives MCP Clients (Cursor, Claude, Windsurf and more) the ability to remember information about users (preferences, behaviors) across conversations.

Installation
Run this command in your terminal to add the MCP server to Claude Code.
Run in terminal:
Command
claude mcp add --transport stdio puliczek-mcp-memory npx -y github:puliczek/mcp-memory

How to use

MCP Memory provides a memory layer for MCP clients by storing user-supplied text and its vector embeddings, then enabling retrieval of relevant memories across conversations. It leverages Cloudflare Workers, Vectorize for vector search, and D1 for persistent storage, orchestrated by a Durable Object and the Agents framework to handle MCP protocol interactions. You can store memories as you chat and retrieve related memories when needed, with similarity-based search ensuring conceptually related items rise to the top even if exact keywords differ.

How to install

Prerequisites:

  • Cloudflare account with access to Workers, Vectorize, D1, and Workers AI
  • Wrangler CLI installed (via npm: npm install -g wrangler) or using the npm scripts provided by the project

Installation steps:

  1. Clone the repository or create a new project from this template
  2. Install dependencies:
npm install
  1. Create a Vectorize index (dimensions 1024, metric cosine):
npx wrangler vectorize create mcp-memory-vectorize --dimensions 1024 --metric cosine
  1. Start the development server locally (requires Cloudflare credentials):
npm run dev
  1. Deploy to Cloudflare once ready:
npm run deploy

Note: If you prefer a one-click setup, use the Cloudflare deployment button in the repository README and follow the prompts to connect your Cloudflare account and select a Vectorize index.

Additional notes

Tips and considerations:

  • Ensure your Cloudflare account has access to Vectorize, D1, and Workers AI enabled for optimal performance.
  • Memory isolation is per-user, so each user’s memories won’t mix with others.
  • The rate limit mentioned (e.g., 100 req/min) is configurable in wrangler.jsonc; adjust as needed for your usage.
  • When running locally, some features like vector search or Workers AI may require Cloudflare service connections.
  • You can customize authentication and add additional security layers if needed beyond the built-in userId-based protection.
  • The MCP protocol integration relies on the Agents framework; make sure your MCP clients are compatible with the expected protocol version.

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