Memory Mcp — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Memory Mcp (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
<!-- mcp-name: io.github.chenxiaofie/memory-mcp -->
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
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 | shRequires Python 3.10 - 3.13 (chromadb is not compatible with Python 3.14+).
Download the vector model (~400MB, one-time):
uvx --from chenxiaofie-memory-mcp memory-mcp-initclaude mcp add memory-mcp -s user -- uvx --from chenxiaofie-memory-mcp memory-mcpHooks 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" }]
}]
}
}claude mcp listYou should see memory-mcp: ... - ✓ Connected.
That's it! Start a new Claude Code session and your conversations will be automatically saved and recalled.
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 SummaryOnce hooks are configured, everything is automatic. Claude will see relevant history from past sessions as context.
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")| Hook | What it does | Timing |
|---|---|---|
| SessionStart | Creates a new episode | ~50ms |
| UserPromptSubmit | Saves user message + retrieves related memories | ~1-2s |
| Stop | Saves assistant response | ~1s |
| SessionEnd | Signals episode closure | ~50ms |
| Tool | Description |
|---|---|
memory_start_episode | Start a new episode |
memory_close_episode | Close and archive current episode |
memory_get_current_episode | Get current active episode |
memory_add_entity | Add a knowledge entity |
memory_confirm_entity | Confirm a detected entity candidate |
memory_reject_candidate | Reject a false detection |
memory_deprecate_entity | Mark an entity as outdated |
memory_get_pending | List pending entity candidates |
memory_recall | Semantic search across episodes and entities |
memory_search_by_type | Search entities by type |
memory_get_episode_detail | Get full episode details |
memory_list_episodes | List all episodes chronologically |
memory_stats | Get system statistics |
memory_encoder_status | Check vector encoder status |
memory_cache_message | Manually cache a message |
memory_clear_cache | Clear message cache |
memory_cleanup_messages | Clean up old cached messages |
| Type | Level | Description |
|---|---|---|
Decision | Project | Technical decisions for this project |
Architecture | Project | Architecture designs |
File | Project | Important file descriptions |
Preference | User | Personal preferences (shared across projects) |
Concept | User | General concepts |
Habit | User | Work habits |
~/.claude-memory/{project-root}/.claude/memory/<details> <summary>Alternative: Install from source</summary>
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.shThen 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</details>
MIT License - see LICENSE file for details.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.