Memory MCP
M

Memory MCP

A persistent memory MCP service designed for Claude Code, which can automatically save conversation histories and intelligently retrieve relevant contexts in subsequent conversations, achieving memory continuity across sessions.
2.5 points
0

What is the Memory MCP Service?

The Memory MCP Service is an intelligent memory system specifically designed for Claude Code. It acts like an assistant that never forgets, automatically recording every conversation you have with Claude and intelligently recalling relevant histories in future conversations. Whether you're developing a project, learning new knowledge, or making plans, it ensures that Claude always understands your background and preferences.

How to use the Memory MCP Service?

It's very simple to use: After installation, configure the automatic hook, and then all conversations will be automatically saved and retrieved. You can also manually call the memory tool to record specific information or search the history. The system supports two storage methods: user - level (shared across projects) and project - level (isolated).

Applicable scenarios

It is suitable for scenarios that require context continuity, such as long - term project development, continuous learning, and complex problem - solving. It is particularly suitable for users such as developers, researchers, and students who need to interact with AI assistants multiple times.

Main features

Automatically save conversations
By configuring hooks, the system can automatically save user messages and AI responses without manual operation.
Semantic search and retrieval
Based on vector embedding technology, it can understand the semantic meaning of queries and find the most relevant historical conversations.
Dual - layer storage architecture
User - level storage (sharing preferences and habits across projects) + Project - level storage (project - specific decisions and architectures).
Knowledge entity extraction
Automatically extract key entities (decisions, preferences, concepts, etc.) from conversations to form a structured knowledge base.
Conversation episode management
Each conversation session is recorded as an "episode", including an automatically generated summary and timestamp.
Claude Code hook integration
Deeply integrated with Claude Code's event system, supporting events such as SessionStart and UserPromptSubmit.
Advantages
๐Ÿš€ Fully automated: No manual operation is required after configuration. Conversations are automatically saved and retrieved.
๐Ÿง  Intelligent association: Find the most relevant historical context based on semantic understanding.
๐Ÿ“Š Structured storage: Convert conversations into searchable knowledge entities.
๐Ÿ”’ Privacy protection: All data is stored locally and not uploaded to the cloud.
โšก Fast response: Retrieving relevant memories usually takes 1 - 2 seconds.
๐Ÿ”„ Continuous across sessions: Ensure context continuity for long - term projects.
Limitations
๐Ÿ“ฆ Approximately 400MB of vector models need to be downloaded for the initial installation.
๐Ÿ Requires Python 3.10 - 3.13 and does not support Python 3.14+.
๐Ÿ’พ Local storage space increases with the growth of conversations.
๐Ÿ”ง Some technical knowledge is required for initial configuration.
๐Ÿ”„ Only supports Claude Code and does not support other AI assistants.

How to use

Install prerequisite tools
First, install uv (Python package manager), which is a prerequisite tool for running the Memory MCP Service.
Initialize the vector model
Download the necessary vector model files (about 400MB, only need to be downloaded once) when using it for the first time.
Add to Claude Code
Add the Memory MCP Service as an MCP server to Claude Code.
Configure automatic hooks (recommended)
Configure automatic hooks to achieve fully automated memory saving and retrieval. Edit the ~/.claude/settings.json file.
Verify the installation
Check if the Memory MCP Service is successfully connected.

Usage examples

Long - term project development
When developing a web application, each session can recall previous architectural decisions, technology selections, and implementation details.
Learning a new framework
When learning the React framework, the system will remember the concepts you have mastered and common problems you have encountered.
Personal preference recording
Record your code style preferences, such as using 2 - space indents, camelCase for function names, etc.

Frequently Asked Questions

Will the Memory MCP Service save my private data?
How long does the installation take?
How to clean up old memory data?
Which Python versions are supported?
Can it still be used if the hooks are not configured?
What is the accuracy of memory retrieval?

Related resources

GitHub repository
Source code and latest updates
PyPI package page
Python package release page
uv installation guide
Installation instructions for the Python package manager uv
Model Context Protocol documentation
Official documentation of the MCP protocol
Claude Code documentation
Claude Code usage guide

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

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