📢 Announcing our research paper: Zentry achieves 26% higher accuracy than OpenAI Memory, 91% lower latency, and 90% token savings! Read the paper to learn how we're revolutionizing AI agent memory.
What is the OpenMemory MCP Server
The OpenMemory MCP Server is a private, local-first memory server that creates a shared, persistent memory layer for your MCP-compatible tools. This runs entirely on your machine, enabling seamless context handoff across tools. Whether you’re switching between development, planning, or debugging environments, your AI assistants can access relevant memory without needing repeated instructions. The OpenMemory MCP Server ensures all memory stays local, structured, and under your control with no cloud sync or external storage.OpenMemory Easy Setup
Prerequisites
- Docker
- OpenAI API Key
OPENAI_API_KEY as a global environment variable:
OPENAI_API_KEY as a parameter to the script:
How the OpenMemory MCP Server Works
Built around the Model Context Protocol (MCP), the OpenMemory MCP Server exposes a standardized set of memory tools:add_memories: Store new memory objectssearch_memory: Retrieve relevant memorieslist_memories: View all stored memorydelete_all_memories: Clear memory entirely
What It Enables
Cross-Client Memory Access
Store context in Cursor and retrieve it later in Claude or Windsurf without repeating yourself.Fully Local Memory Store
All memory is stored on your machine. Nothing goes to the cloud. You maintain full ownership and control.Unified Memory UI
The built-in OpenMemory dashboard provides a central view of everything stored. Add, browse, delete and control memory access to clients directly from the dashboard.Supported Clients
The OpenMemory MCP Server is compatible with any client that supports the Model Context Protocol. This includes:- Cursor
- Claude Desktop
- Windsurf
- Cline, and more.
Real-World Examples
Scenario 1: Cross-Tool Project Flow
Define technical requirements of a project in Claude Desktop. Build in Cursor. Debug issues in Windsurf - all with shared context passed through OpenMemory.Scenario 2: Preferences That Persist
Set your preferred code style or tone in one tool. When you switch to another MCP client, it can access those same preferences without redefining them.Scenario 3: Project Knowledge
Save important project details once, then access them from any compatible AI tool, no more repetitive explanations.Conclusion
The OpenMemory MCP Server brings memory to MCP-compatible tools without giving up control or privacy. It solves a foundational limitation in modern LLM workflows: the loss of context across tools, sessions, and environments. By standardizing memory operations and keeping all data local, it reduces token overhead, improves performance, and unlocks more intelligent interactions across the growing ecosystem of AI assistants. This is just the beginning. The MCP server is the first core layer in the OpenMemory platform - a broader effort to make memory portable, private, and interoperable across AI systems.Getting Started Today
- Repository: GitHub
- Join our community: [Telegram](https://t.me/zentrycommunity