Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@SelfMemory search for my notes about car maintenance"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Store AI memories for you and your agents
It is a open-source universal memory engine where users can store and retrieve their AI conversations and context across different models. Users can add memories through MCP, SDK, or a website selfmemory.com Over time, this will evolve into a one-stop memory hub with note-taking and chatbot features. For B2B, it becomes a knowledge backbone, storing project context, organizational knowledge, documents, and data sources to power company-wide AI systems.
pip install selfmemoryfrom selfmemory import SelfMemory
memory = SelfMemory()
# Add memories
memory.add("Can you find the nearest BMW car showroom for me.", user_id="user")
# Search memories
results = memory.search("Can you find a car washing service near me?", user_id="user")
print(results)Related MCP server: Mnemexa MCP
Visit docs.selfmemory.com for complete documentation, guides, and examples.
Changelog: See CHANGELOG.md for a detailed list of changes and updates.
We welcome contributions! CONTRIBUTING.md.
Discord: discord.com/invite/selfmemory
Brand Assets (Logos, Slides, etc.): Storage Link
This server cannot be deployed
A persistent AI self you own — memory, persona, judgment — portable across all your AI hosts.
A self-improving memory layer. Your memory, notes, tasks and goals, remembered everywhere.
Personal AI memory — gives every AI agent shared, persistent memory of you
Person-owned AI memory that learns, not just stores — portable context for any MCP client.
