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Memory Mcp

chenxiaofie/memory-mcp
11STDIOregistry active
Summary

Adds persistent memory to Claude Code by automatically saving and retrieving conversation context across sessions. Uses vector embeddings to store two types of knowledge: episodes (full conversation sessions with summaries) and entities (extracted decisions, preferences, and concepts). Integrates via hooks in Claude Code's settings.json to auto-save messages on UserPromptSubmit and Stop events, then injects relevant history from past sessions as context. Exposes tools like memory_recall for semantic search, memory_add_entity for manual knowledge capture, and memory_start_episode for session management. Storage splits between user-level (~/.claude-memory) for cross-project preferences and project-level (.claude/memory) for project-specific decisions. Requires a one-time 400MB model download and Python 3.10-3.13. Useful when you want Claude to remember architectural decisions, coding preferences, or project context without re-explaining everything each session.

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Memory MCP Service

PyPI version Python License: MIT

English | 中文

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. Memory recall demo - retrieving past session history

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

HookWhat it doesTiming
SessionStartCreates a new episode~50ms
UserPromptSubmitSaves user message + retrieves related memories~1-2s
StopSaves assistant response~1s
SessionEndSignals episode closure~50ms

Tools Reference

ToolDescription
memory_start_episodeStart a new episode
memory_close_episodeClose and archive current episode
memory_get_current_episodeGet current active episode
memory_add_entityAdd a knowledge entity
memory_confirm_entityConfirm a detected entity candidate
memory_reject_candidateReject a false detection
memory_deprecate_entityMark an entity as outdated
memory_get_pendingList pending entity candidates
memory_recallSemantic search across episodes and entities
memory_search_by_typeSearch entities by type
memory_get_episode_detailGet full episode details
memory_list_episodesList all episodes chronologically
memory_statsGet system statistics
memory_encoder_statusCheck vector encoder status
memory_cache_messageManually cache a message
memory_clear_cacheClear message cache
memory_cleanup_messagesClean up old cached messages

Entity Types

TypeLevelDescription
DecisionProjectTechnical decisions for this project
ArchitectureProjectArchitecture designs
FileProjectImportant file descriptions
PreferenceUserPersonal preferences (shared across projects)
ConceptUserGeneral concepts
HabitUserWork habits

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.

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Configuration

CLAUDE_PROJECT_ROOT

项目根目录路径

Categories
AI & LLM Tools
Registryactive
Packagechenxiaofie-memory-mcp
TransportSTDIO
UpdatedFeb 12, 2026
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