mcp-memory

<div align="center" >🤝 Show your support - give a ⭐️ if you liked the content </div> --- # 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**. It uses vector search technology to find relevant memories based on meaning, not just keywords. It's built with Cloudflare Workers, D1, Vectorize (RAG), Durable Objects, Workers AI and Agents. ## 📺 Video <a href="https://www.youtube.com/watch?feature=player_embedded&v=qfFvYERw2TQ" target="_blank"> <img src="https://github.com/Puliczek/mcp-memory/blob/main/video.png?raw=true" alt="Watch the video" width="800" height="450" border="10" /> </a> ## 🚀 Try It Out ### [https://memory.mcpgenerator.com/](https://memory.mcpgenerator.com/) ## 🛠️ How to Deploy Your Own MCP Memory ### Option 1: One-Click Deploy Your Own MCP Memory to Cloudflare [](https://deploy.workers.cloudflare.com/?url=https://github.com/puliczek/mcp-memory) In **Create Vectorize** section choose: - **Dimensions:** 1024 - **Metric:** cosine Click button **"Create and Deploy"** In Cloudflare dashboard, go to "Workers & Pages" and click on Visit  ### Option 2: Use this template 1. Click the "Use this template" button at the top of this repository 2. Clone your new repository 3. Follow the setup instructions below ### Option 3: Create with CloudFlare CLI ```bash npm create cloudflare@latest --git https://github.com/puliczek/mcp-memory ``` ## 🔧 Setup (Only Option 2 & 3) 1. Install dependencies: ```bash npm install ``` 2. Create a Vectorize index: ```bash npx wrangler vectorize create mcp-memory-vectorize --dimensions 1024 --metric cosine ``` 3. Install Wrangler: ```bash npm run dev ``` 4. Deploy the worker: ```bash npm run deploy ``` ## 🧠 How It Works  1. **Storing Memories**: - Your text is processed by **Cloudflare Workers AI** using the open-source `@cf/baai/bge-m3` model to generate embeddings - The text and its vector embedding are stored in two places: - **Cloudflare Vectorize**: Stores the vector embeddings for similarity search - **Cloudflare D1**: Stores the original text and metadata for persistence - A **Durable Object** (MyMCP) manages the state and ensures consistency - The **Agents** framework handles the **MCP protocol** communication 2. **Retrieving Memories**: - Your query is converted to a vector using **Workers AI** with the same `@cf/baai/bge-m3` model - Vectorize performs similarity search to find relevant memories - Results are ranked by similarity score - The **D1 database** provides the original text for matched vectors - The **Durable Object** coordinates the retrieval process This architecture enables: - Fast vector similarity search through Vectorize - Persistent storage with D1 - Stateful operations via Durable Objects - Standardized AI interactions through Workers AI - Protocol compliance via the Agents framework The system finds conceptually related information even when the exact words don't match. ## 🔒 Security MCP Memory implements several security measures to protect user data: - Each user's memories are stored in **isolated namespaces** within Vectorize for data separation - Built-in **rate limiting** prevents abuse (**100 req/min** - you can change it in wrangler.jsonc) - **Authentication is based on userId only** - While this is sufficient for basic protection due to rate limiting - Additional authentication layers (like API keys or OAuth) can be easily added if needed - All data is stored in Cloudflare's secure infrastructure - All communications are secured with industry-standard TLS encryption (automatically provided by Cloudflare's SSL/TLS certification) ## 💰 Cost Information - FREE for Most Users MCP Memory is free to use for normal usage levels: - Free tier allows 1,000 memories with ~28,000 queries per month - Uses Cloudflare's free quota for Workers, Vectorize, Worker AI and D1 database For more details on Cloudflare pricing, see: - [Vectorize Pricing](https://developers.cloudflare.com/vectorize/platform/pricing/) - [Workers AI Pricing](https://developers.cloudflare.com/workers-ai/pricing-and-rate-limits/) - [Workers Pricing](https://developers.cloudflare.com/workers/platform/pricing/) - [Durable Objects Pricing](https://developers.cloudflare.com/durable-objects/platform/pricing/) - [Database D1 Pricing](https://developers.cloudflare.com/d1/platform/pricing/) ## ❓ FAQ 1. **Can I use memory.mcpgenerator.com to store my memories?** - Yes, you can use memory.mcpgenerator.com to store and retrieve your memories - The service is free - Your memories are securely stored and accessible only to you - I cannot guarantee that the service will always be available 2. **Can I host it?** - Yes, you can host your own instance of MCP Memory **for free on Cloudflare** - You'll need a Cloudflare account and the following services: - Workers - Vectorize - D1 Database - Workers AI 3. **Can I run it locally?** - Yes, you can run MCP Memory locally for development - Use `wrangler dev` to run the worker locally - You'll need to set up local development credentials for Cloudflare services - Note that some features like vector search or workers AI requires a connection to Cloudflare's services 4. **Can I use different hosting?** - No, MCP Memory is specifically designed for Cloudflare's infrastructure 5. **Why did you build it?** - I wanted an open-source solution - Control over my own data was important to me 6. **Can I use it for more than one person?** - Yes, MCP Memory can be integrated into your app to serve all your users - Each user gets their own isolated memory space 7. **Can I use it to store things other than memories?** - Yes, MCP Memory can store any type of text-based information - Some practical examples: - Knowledge Base: Store technical documentation, procedures, and troubleshooting guides - User Behaviors: Track how users interact with features and common usage patterns - Project Notes: decisions and project updates - The vector search will help find related items regardless of content type # 🤝 Show your support <div>🤝 Show your support - give a ⭐️ if you liked the content</div>