memory-mcp
Integrates with Supabase to persist project memory data, including notes, project details, decision history, and context across AI tool sessions.
Click on "Install 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., "@memory-mcpremember we decided to use PostgreSQL for the database"
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.
๐ง memory-mcp - Keep Project Memory in Sync
๐ What memory-mcp does
memory-mcp helps you keep project memory in one place. It works with OpenCode, Antigravity, Claude Code, and Codex through the Model Context Protocol, or MCP.
Use it to store notes, project details, and past decisions in Supabase. That lets your AI tools remember what matters across sessions.
๐ฅ๏ธ Windows setup
This guide is for Windows users who want to get started fast.
You will need:
A Windows 10 or Windows 11 PC
An internet connection
A web browser
Access to a Supabase account
An AI tool that supports MCP, such as Claude Code, OpenCode, Antigravity, or Codex
๐ฅ Download memory-mcp
Visit this page to download and set up memory-mcp:
https://github.com/User75621/memory-mcp
If the page has a release file, download it. If it has setup files or source code, save the files to your PC so you can run the server from that folder.
โ๏ธ Set up Supabase
memory-mcp stores project memory in Supabase. You need a Supabase project before you start.
Go to Supabase and sign in.
Create a new project.
Save your project URL.
Save your API keys.
Keep the database settings for later use.
You also need a table for memory data. Use the schema included in the repository if it is provided. If not, create a table for notes, project IDs, timestamps, and message text.
๐งฉ Install Python
memory-mcp uses Python on Windows.
Open the Python website.
Download Python 3.11 or newer.
Run the installer.
Check the box for Add Python to PATH.
Finish the install.
To confirm it works, open Command Prompt and run:
python --version
๐ Open the folder
After you download the files, put them in a folder such as:
C:\memory-mcp
Open that folder in File Explorer.
If the repository contains a requirements file, use it to install the needed packages.
๐ ๏ธ Install the needed packages
Open Command Prompt in the memory-mcp folder and run:
pip install -r requirements.txt
If the project uses another package file, use that file instead.
๐ Add your Supabase settings
memory-mcp needs your Supabase details to connect to your memory store.
Create a file named .env in the project folder and add your values:
SUPABASE_URL=your_supabase_url SUPABASE_KEY=your_supabase_key SUPABASE_TABLE=your_table_name
If the project includes sample settings, copy that format and fill in your own values.
โถ๏ธ Run memory-mcp
In Command Prompt, stay in the project folder and run:
python main.py
If the repository uses a different start file, run the main file that starts the MCP server.
When the server starts, it will stay open and listen for requests from your AI tool.
๐ Connect it to your AI tool
Add memory-mcp to the MCP setup for your tool.
Use the server command or file path from the project files, then point it to the Python file that starts the service.
A common setup looks like this:
Server name: memory-mcp
Command: python
Arguments: path to the start file
Environment: your Supabase settings
Then restart your AI tool.
๐ How to use it
Once connected, your AI tool can store and read project memory.
You can use it for:
Project goals
Decision history
Task notes
File context
User preferences
Long-term project facts
This helps the tool keep track of work across chats and sessions.
๐งช Check that it works
Try a simple test:
Add a note in your AI tool.
Ask it to save the note to memory.
Close the tool.
Open it again.
Ask for the saved note.
If the setup is correct, the tool will pull the same memory from Supabase.
๐ง Common fixes
If the server does not start:
Check that Python is installed
Check that you are in the right folder
Check that the
.envfile has the correct valuesCheck that your Supabase table exists
Restart Command Prompt and try again
If your AI tool cannot see the server:
Confirm the MCP config points to the right Python file
Make sure the server is running
Restart the AI tool after changes
If memory does not save:
Check the Supabase key
Check table access rules
Confirm the table name matches your settings
๐ Folder layout
A simple project layout may look like this:
main.pyโ starts the serverrequirements.txtโ lists Python packages.envโ stores your Supabase valuesREADME.mdโ setup notessrc/โ app codeschemas/โ database setup files
๐ Privacy and data
memory-mcp stores project memory in your own Supabase project. That gives you control over where the data lives and who can access it.
Use a private Supabase project and keep your keys safe.
๐ง Best use cases
memory-mcp works well for:
Personal project notes
Team project memory
AI coding sessions
Research logs
Repeated task context
Long project work that spans many days
๐ Useful link
Download and setup page:
https://github.com/User75621/memory-mcp
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