Memory MCP

Memory MCP Service

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A persistent memory MCP service for Claude Code. Automatically saves conversations and retrieves relevant history across sessions.

What it does: Every time you chat with Claude Code, your conversation context (decisions, preferences, key discussions) is saved and automatically recalled in future sessions — so Claude always has the background it needs.

Quick Start

Prerequisites

Install uv (Python package runner):

# Windows

powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

Mac/Linux

curl -LsSf https://astral.sh/uv/install.sh | sh

Requires Python 3.10 - 3.13 (chromadb is not compatible with Python 3.14+).

1. Initialize (First Time Only)

Download the vector model (~400MB, one-time):

uvx --from chenxiaofie-memory-mcp memory-mcp-init

2. Add MCP Server to Claude Code

claude mcp add memory-mcp -s user -- uvx --from chenxiaofie-memory-mcp memory-mcp

3. Configure Hooks (Recommended)

Hooks enable fully automatic message saving. Without hooks, you need to manually call memory tools.

Add the following to ~/.claude/settings.json:

{

"hooks": { "SessionStart": [{ "matcher": ".*", "hooks": [{ "type": "command", "command": "uvx --from chenxiaofie-memory-mcp memory-mcp-session-start" }] }], "UserPromptSubmit": [{ "matcher": ".*", "hooks": [{ "type": "command", "command": "uvx --from chenxiaofie-memory-mcp memory-mcp-auto-save" }] }], "Stop": [{ "matcher": ".*", "hooks": [{ "type": "command", "command": "uvx --from chenxiaofie-memory-mcp memory-mcp-save-response" }] }], "SessionEnd": [{ "matcher": ".*", "hooks": [{ "type": "command", "command": "uvx --from chenxiaofie-memory-mcp memory-mcp-session-end" }] }] } }

4. Verify

claude mcp list

You should see memory-mcp: ... - ✓ Connected.

That's it! Start a new Claude Code session and your conversations will be automatically saved and recalled.

How It Works

Session Start ──► Create Episode ──► Monitor Process (background)

│ User Message ──► Save Message ──► Recall Related Memories ──► Inject Context │ Claude Reply ──► Save Response │ │ Session End ──► Close Signal ──► Archive Episode + Generate Summary

• Episodes: Each conversation session is an "episode" with auto-generated summaries
• Entities: Key knowledge extracted from conversations (decisions, preferences, concepts)
• Dual-layer storage: User-level (shared across projects) + Project-level (isolated per project)
• Semantic search: Vector-based retrieval finds relevant past context

Usage

Automatic Mode (With Hooks)

Once hooks are configured, everything is automatic. Claude will see relevant history from past sessions as context.

Manual Mode

You can also call memory tools directly in Claude Code:

# Start a new episode

memory_start_episode("Login Feature Development", ["auth"])

Record a decision

memory_add_entity("Decision", "Use JWT + Redis", "For distributed deployment")

Search history

memory_recall("login implementation")

Close episode

memory_close_episode("Completed JWT login feature")

Hooks Reference

Tools Reference

Entity Types

Storage Locations

• User-level: ~/.claude-memory/
• Project-level: {project-root}/.claude/memory/

Alternative: Install from source

If you need to run from source (e.g., for development):

git clone https://github.com/chenxiaofie/memory-mcp.git

cd memory-mcp

Windows:

install.bat

Mac/Linux:

chmod +x install.sh && ./install.sh

Then configure MCP server with the venv Python:

# Windows:

claude mcp add memory-mcp -s user -- "C:\path\to\memory-mcp\venv310\Scripts\python.exe" -m memory_mcp.server

Mac/Linux:

claude mcp add memory-mcp -s user -- /path/to/memory-mcp/venv310/bin/python -m memory_mcp.server

Author

陈佳俊 (Jiajun Chen) — front-end engineer based in Hangzhou, China. GitHub @chenxiaofie · feifeichen1999@gmail.com

本项目由陈佳俊（GitHub: chenxiaofie）开发并维护。

License

MIT License - see LICENSE file for details.