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Health: ActiveRecent health check succeeded.Last checked 9/7/2026, 6:57:54 PM

Memory MCP

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe havenโ€™t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time โ€” check back soon.
View Repository11 GitHub StarsTotal stargazers on GitHub for the source repository (11 stars).Visit Website

A scenario + entity memory MCP service that provides persistent memory capabilities for Claude Code.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag โ€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON โ–พ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "memory-mcp-2": {
      "command": "uvx",
      "args": [
        "--from"
      ]
    }
  }
}

๐Ÿ’ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives๐Ÿง  More in Knowledge & Memory

Documentation Overview

Memory MCP Service

PyPI version Python License: MIT

English | ไธญๆ–‡

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 โ€” so Claude always has the background it needs. Memory recall demo - retrieving past session history

Quick Start

Prerequisites

Install uv (Python package runner):

bash
# 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):

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

2. Add MCP Server to Claude Code

Terminal
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:

config.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

Terminal
claude mcp list

You should see memory-mcp: ... - โœ“ Connected.

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

How It Works

Code
Session Start โ”€โ”€โ–บ Create Episode โ”€โ”€โ–บ Monitor Process (background)
                                          โ”‚
User Message  โ”€โ”€โ–บ Save Message โ”€โ”€โ–บ Recall Related Memories โ”€โ”€โ–บ Inject Context
                                          โ”‚
Claude Reply  โ”€โ”€โ–บ Save Response           โ”‚
                                          โ”‚
Session End   โ”€โ”€โ–บ Close Signal โ”€โ”€โ–บ 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:

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):

bash
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:

bash
# 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

้™ˆไฝณไฟŠ (Jiajun Chen) โ€” front-end engineer based in Hangzhou, China. GitHub @chenxiaofie ยท feifeichen1999@gmail.com

ๆœฌ้กน็›ฎ็”ฑ้™ˆไฝณไฟŠ๏ผˆGitHub: chenxiaofie๏ผ‰ๅผ€ๅ‘ๅนถ็ปดๆŠคใ€‚

License

MIT License - see LICENSE file for details.

Read the full README โ†’View source on GitHub โ†’

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Reviews

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Frequently Asked Questions about Memory MCP

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "memory-mcp": { "command": "npx", "args": ["-y", "memory-mcp"] } }

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Technical Specs & Signals

Category๐Ÿง Knowledge & Memory
More technical detailsExpand โ–พ
TransportSTDIO
RuntimePython
Last updatedSep 7, 2026
Views0
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars11
GitHub Star CountTotal stargazers on GitHub representing community popularity (11 stars).
39Quality signal: Fair ยท 39/100How this signal is calculated โ–พ
Server availabilityNot measured

Not scored for repo-hosted servers โ€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools16/30
Adoption & activity3/15
Community engagement0/10

A guidance signal from public completeness & health data โ€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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