Memory Engine MCP
Overview
Description from the maker (original English)
Local-first graph memory for AI assistants with SQLite, semantic search, and MCP tools.
What you can do with it
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
- Connection: Runs on your computer
- Transport: SSE
- Category: Search & AI memory
Install
Pick the AI app you use, then copy the settings.
Passed 2/2 checks · Runs on your computer
First: which AI do you use?
Pick your app and the steps appear below.
Works with Claude, with some setup first
You need a Memory Engine MCP key (sign up on the maker’s site, may cost money) · Install Docker on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone
Install Docker
One time only; it works for every server that needs Docker
Sign up and create a Memory Engine MCP key
Open the maker’s site, sign up and create an API key for the next step. It may cost money.
How to get a key is in the maker’s README below
Open the Claude desktop app’s settings file
SettingsDeveloperEdit Config
Paste these settings and save the file
{ "mcpServers": { "memory-engine": { "command": "docker", "args": [ "run", "-i", "--rm", "-e", "MEMORY_DB_PATH", "-e", "MARKDOWN_SOURCE", "-e", "MEMORY_PORT", "ghcr.io/simoneb79/memory-engine-mcp:1.5.3" ], "env": { "MEMORY_DB_PATH": "your-value", "MARKDOWN_SOURCE": "your-value", "MEMORY_PORT": "your-value" } } } }Paste the key only into the app’s field, never into a chat or to anyone
Quit Claude and open it again
Try it
Use Memory Engine MCP and tell me what you can do for me, then show me one thing✓ If Claude says it is using Memory Engine MCP or shows a Memory Engine MCP tool in the answer, you are connected
Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version
ChatGPT cannot connect Memory Engine MCP yet
Memory Engine MCP runs on your computer, but ChatGPT can only connect servers that run on the web
What you can do instead
A · Use an app that can connect Memory Engine MCP
- You need a Memory Engine MCP key (sign up on the maker’s site, may cost money) · Install Docker on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone
- You need a Memory Engine MCP key (sign up on the maker’s site, may cost money) · Install Docker on your computer first (one time)
- You need a Memory Engine MCP key (sign up on the maker’s site, may cost money) · Install Docker on your computer first (one time)
- You need a Memory Engine MCP key (sign up on the maker’s site, may cost money) · Install Docker on your computer first (one time)
B · Others in Search & AI memory that work with ChatGPT
Picked from the most used in the same category, only ones that connect by address with no key
- AIHOT✓ ChatGPT
- Sui Knowledge Base (kapa.ai)✓ ChatGPT
- Exa✓ ChatGPT
Works with Claude Code, with some setup first
You need a Memory Engine MCP key (sign up on the maker’s site, may cost money) · Install Docker on your computer first (one time)
Install Docker
One time only; it works for every server that needs Docker
Sign up and create a Memory Engine MCP key
Open the maker’s site, sign up and create an API key for the next step. It may cost money.
How to get a key is in the maker’s README below
Open Terminal
Mac: press Command+Space and type Terminal · Windows: open PowerShell
Paste this command and press Enter
claude mcp add memory-engine --env MEMORY_DB_PATH=your-value --env MARKDOWN_SOURCE=your-value --env MEMORY_PORT=your-value -- docker run -i --rm -e MEMORY_DB_PATH -e MARKDOWN_SOURCE -e MEMORY_PORT ghcr.io/simoneb79/memory-engine-mcp:1.5.3Replace “your-value” with your key before pressing Enter
Paste the key only into the app’s field, never into a chat or to anyone
Type /mcp in Claude Code
You should see Memory Engine MCP listed as connected
Try it
Use Memory Engine MCP and tell me what you can do for me, then show me one thing✓ If Claude Code says it is using Memory Engine MCP or shows a Memory Engine MCP tool in the answer, you are connected
Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Works with Cursor, with some setup first
You need a Memory Engine MCP key (sign up on the maker’s site, may cost money) · Install Docker on your computer first (one time)
Install Docker
One time only; it works for every server that needs Docker
Sign up and create a Memory Engine MCP key
Open the maker’s site, sign up and create an API key for the next step. It may cost money.
How to get a key is in the maker’s README below
Fill in your key
In the Memory Engine MCP settings, MEMORY_DB_PATH, MARKDOWN_SOURCE, MEMORY_PORT is empty; add your key and save
Paste the key only into the app’s field, never into a chat or to anyone
Open the AI chat in Cursor in Agent mode
Try it
Use Memory Engine MCP and tell me what you can do for me, then show me one thing✓ If Cursor says it is using Memory Engine MCP or shows a Memory Engine MCP tool in the answer, you are connected
Menu names checked against Cursor’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Works with VS Code, with some setup first
You need a Memory Engine MCP key (sign up on the maker’s site, may cost money) · Install Docker on your computer first (one time)
Install Docker
One time only; it works for every server that needs Docker
Sign up and create a Memory Engine MCP key
Open the maker’s site, sign up and create an API key for the next step. It may cost money.
How to get a key is in the maker’s README below
Fill in your key
In the Memory Engine MCP settings, MEMORY_DB_PATH, MARKDOWN_SOURCE, MEMORY_PORT is empty; add your key and save
Paste the key only into the app’s field, never into a chat or to anyone
Open the AI chat in VS Code in Agent mode
Try it
Use Memory Engine MCP and tell me what you can do for me, then show me one thing✓ If VS Code says it is using Memory Engine MCP or shows a Memory Engine MCP tool in the answer, you are connected
Menu names checked against VS Code’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Other apps that use MCP, such as Windsurf, Zed or Gemini CLI, each add servers differently. See how in the app list.
JSON settings are under “For developers” below
For developers: Terminal commands and JSON settings
Installed on your computer
Claude Code
claude mcp add memory-engine --env MEMORY_DB_PATH=your-value --env MARKDOWN_SOURCE=your-value --env MEMORY_PORT=your-value -- docker run -i --rm -e MEMORY_DB_PATH -e MARKDOWN_SOURCE -e MEMORY_PORT ghcr.io/simoneb79/memory-engine-mcp:1.5.3Claude Desktop (claude_desktop_config.json)
{
"mcpServers": {
"memory-engine": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"MEMORY_DB_PATH",
"-e",
"MARKDOWN_SOURCE",
"-e",
"MEMORY_PORT",
"ghcr.io/simoneb79/memory-engine-mcp:1.5.3"
],
"env": {
"MEMORY_DB_PATH": "your-value",
"MARKDOWN_SOURCE": "your-value",
"MEMORY_PORT": "your-value"
}
}
}
}Cursor (~/.cursor/mcp.json)
{
"mcpServers": {
"memory-engine": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"MEMORY_DB_PATH",
"-e",
"MARKDOWN_SOURCE",
"-e",
"MEMORY_PORT",
"ghcr.io/simoneb79/memory-engine-mcp:1.5.3"
],
"env": {
"MEMORY_DB_PATH": "your-value",
"MARKDOWN_SOURCE": "your-value",
"MEMORY_PORT": "your-value"
}
}
}
}VS Code (mcp.json)
{
"servers": {
"memory-engine": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"MEMORY_DB_PATH",
"-e",
"MARKDOWN_SOURCE",
"-e",
"MEMORY_PORT",
"ghcr.io/simoneb79/memory-engine-mcp:1.5.3"
],
"env": {
"MEMORY_DB_PATH": "your-value",
"MARKDOWN_SOURCE": "your-value",
"MEMORY_PORT": "your-value"
}
}
}
}Values you fill in
MEMORY_DB_PATHenvSQLite database path inside the container.MARKDOWN_SOURCEenvOptional directory for one-way markdown import.MEMORY_PORTenvSSE server port. Default: 8085.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
At a glance
Which apps can use it
Based on how this server connects and on each app’s own docs, checked Nov 10, 2026.
Run on your computer in
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
Related guides
What it can do
Runs on your computer; the tool list appears in your AI app after you install it.
Basic checksi
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 11, 2026
- ✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account SimoneB79, which owns the repo
- ✓ Pass
Still maintained
Code last changed 20 days ago
- … Not checked yet
Has a licence
We have not read this repo from GitHub yet
- – Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
- – Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
- … Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints
Discussion
Ask, share a tip or report that it does not work. Sorted by what people marked helpful.
No posts yet. Be the first to ask or share.
Posts here are written by users, not the PopNx team.
User reviews
No reviews yet
Compared with others in Search & AI memoryi
- More stars than 75% of the other 5875 servers in this category
- Published to the registry more recently than 22% of the other 5875 servers in this category
- Basic checks equal to or better than 100% of the other 5875 servers in this category
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
Common questions
Is Memory Engine MCP safe?
It passed 2 of 2 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
What keys or codes does it need?
The registry does not list a required key, though some servers ask you to sign in on first use.
Does it run on my computer or in the cloud?
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
Is it still maintained?
The GitHub repo last changed 20 days ago, and the latest version (1.5.3) reached the registry 4 months ago.
Which apps can use it?
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.
What can I use instead?
In the same category: Ruflo, Context7, Metabase
Alternatives
Servers in the same category from other makers, sorted by stars.
Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
README from the maker
Open the README
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
🧠 Memory Engine MCP
Local-first, graph-aware long-term memory for AI assistants.
SQLite + semantic search + knowledge graph + MCP tools for agents that need continuity.
Works with Claude Desktop · Claude Code · Cursor · Cline · Windsurf · OpenClaw · any MCP client
Why Memory Engine?
Most MCP memory servers are either simple key-value stores or plain text search wrappers.
Memory Engine is different: it models memory as typed atoms connected by typed bonds, then retrieves context with a hybrid ranking pipeline that combines:
- full-text search (SQLite FTS5)
- semantic similarity via local Ollama embeddings
- confidence, recency, and weight
- graph expansion from related memories
The goal is not just storage. The goal is a memory system that can recall, connect, decay, curate, and learn over time.
Highlights
- Local-first — SQLite database, optional local embeddings via Ollama, no required cloud API.
- MCP-native — exposes 35 tools through FastMCP.
- Graph-aware recall — expands top hits through bidirectional bonds for richer context.
- Semantic search — meaning-based retrieval with
nomic-embed-text. - Markdown coexistence — import existing notes one-way without replacing your human-readable memory.
- Error memory — remembers mistakes and corrections, with auto-promotion to preferences after repeated failures.
- Cognitive curator — non-destructive maintenance pass for compaction, bond suggestions, duplicate detection, and isolated atom classification.
- Session watcher — canonical OpenClaw SQLite ingestion (schema 17), reset-aware digests, and JSONL legacy fallback.
- Backup & restore — full SQLite snapshots, JSON export/import, verified restores with automatic safety backups.
- Auth & hardening — optional API token, secure bind, input validation, rate limiting.
- Test suite — 144 tests covering CRUD, ranking, migrations, auth, backup, concurrency, and transcript ingestion.
- Benchmark — CLI recall quality suite with Precision@K, MRR, latency percentiles.
Architecture
AI assistant / MCP client
│ ▼ FastMCP server — 35 tools │ ▼ Memory engine — hybrid ranking, graph recall, decay, learning │ ├── SQLite — atoms, bonds, FTS5, JSON metadata, versions ├── Ollama — optional local embeddings ├── Curator — conservative maintenance └── Session watcher — OpenClaw SQLite + JSONL fallback
MCP Tools
Memory
| Tool | Purpose |
|---|---|
remember | Create or update an atom |
recall | Smart hybrid recall with graph expansion |
working_set | Build a task-oriented context pack |
semantic_search | Pure semantic search |
get_atom | Read one atom with bonds |
list_atoms | Browse atoms by domain/type/status |
merge_atoms | Merge duplicate atoms |
export_atom | Export one atom as markdown |
Knowledge graph
| Tool | Purpose |
|---|---|
link / unlink | Create or remove typed bonds |
search_graph | Traverse the graph from one atom |
suggest_bonds | Suggest bonds for one atom |
suggest_bonds_all | Suggest or create bonds in bulk |
Learning and maintenance
| Tool | Purpose |
|---|---|
curator_run | Conservative curation pass |
cognitive_status | Graph and memory health metrics |
learning_run | Detect contradictions, weak atoms, merge candidates, gaps |
ask_pending / answer_human | Human-in-the-loop clarification |
decay_run | Run decay cycle |
cleanup_sessions | Remove expired session atoms |
cleanup_duplicates | Remove duplicate session atoms |
reindex_embeddings | Rebuild embeddings |
Error memory and preferences
| Tool | Purpose |
|---|---|
error_check | Check past failures before doing a task |
error_log | Record a mistake and the correction |
error_list | Browse unresolved/resolved errors |
preference_search | Search structured preferences |
Import and introspection
| Tool | Purpose |
|---|---|
import_markdown | Import markdown notes into atoms |
memory_summary | 3-level summary: global → domain → detail |
stats | Database statistics |
version | Server version |
recall_session | Search one OpenClaw session |
session_summary | Summarize one OpenClaw session |
memory_contradict | Supersede an old atom with a newer contradictory one |
list_contradictions | List explicit contradiction/supersession records |
classify_memory_tier | Infer the 3-tier class (episodic/semantic/procedural) |
memory_impact | Impact analysis: what depends on this atom |
Backup, restore & export
| Tool | Purpose |
|---|---|
backup_database | Create, list, verify, or clean up SQLite snapshots |
restore_database | Restore from a backup (with automatic safety backup) |
export_all | Export all memory data as portable JSON |
import_data | Import from JSON (merge or replace mode) |
Web UI (optional)
Memory Engine includes an optional web UI for graph exploration, atom inspection, contradiction browsing, and impact analysis.
# In docker-compose.yml, add:
environment:
- MEM_UI_PORT=6000
expose:
- "6000"
Or run standalone:
python3 web_ui.py
Open http://localhost:6000
Web UI: interactive graph, atom details, contradiction browser, stats dashboard
Quick start with Docker
Option A — Use the pre-built image (recommended)
# docker-compose.yml
services: memory-engine: image: ghcr.io/simoneb79/memory-engine-mcp:2.1.0 ports:
- "8085:8085" volumes:
- memory-data:/data restart: unless-stopped
volumes: memory-data:
docker compose up -d
Pin the version. Use an explicit tag like
:1.7.0in production.
Avoid
:latest— it can change without notice.
Option B — Build from source
git clone https://github.com/SimoneB79/memory-engine-mcp.git
cd memory-engine-mcp cp docker-compose.yml docker-compose.local.yml
Edit volume paths in docker-compose.local.yml if needed
docker compose -f docker-compose.local.yml up -d --build
Default endpoint:
http://localhost:8085/sse
Example MCP client config:
{
"mcpServers": { "memory-engine": { "url": "http://localhost:8085/sse", "transport": "sse" } } }
See docs/INSTALL.md for Docker, local Python, Claude Desktop, Cursor, and OpenClaw examples.
Local Python
python -m venv .venv
source .venv/bin/activate pip install -r requirements.txt python server.py
Configuration
Main configuration file: config.json
Important environment variables:
| Variable | Default | Purpose |
|---|---|---|
MEMORY_DB_PATH | /data/memory.db | SQLite database path |
MARKDOWN_SOURCE | /workspace/memory | Markdown directory for import |
MEMORY_HOST | 127.0.0.1 | Server bind address (secure default) |
MEMORY_PORT | 8085 | SSE port |
MEMORY_API_TOKEN | _(none)_ | Optional API token for auth (see Security) |
OPENCLAW_AGENT_DB | _(none)_ | Preferred per-agent OpenClaw SQLite DB (schema 17) |
OPENCLAW_SESSIONS_DIR | /sessions | Legacy JSONL fallback when no agent DB is configured |
SESSION_DIGEST_DIR | /data/session_digests | Optional session digest output |
For the SQLite mount, WAL/SHM handling, filtering, and security boundary, see OpenClaw transcript ingestion.
Semantic search requires Ollama reachable from the container or host. Default:
{
"ollama": { "enabled": true, "host": "http://ollama:11434", "model": "nomic-embed-text" } }
If you do not use Ollama, set ollama.enabled to false; FTS recall still works.
Memory model
Atoms have:
titlebodytype:fact,decision,event,preference,log,procedure,note, etc.domain: project or topic namespaceconfidenceweighttags- optional TTL
Bonds connect atoms with relation types:
is_a · part_of · depends_on · contradicts · refines · derived_from · detail_of · related_to
Example usage
remember(
title="Use PostgreSQL for analytics", body="SQLite is kept for local memory, PostgreSQL is used for multi-user analytics.", type="decision", domain="project:analytics", confidence=0.9, tags=["database", "architecture"] )
recall(query="what database did we choose for analytics?", limit=5)
working_set(
query="continue the analytics backend work", domain="project:analytics", limit=8, graph_depth=1 )
Security
By default, Memory Engine runs in open mode (no auth) — safe for stdio or trusted local environments.
To enable API token auth:
// config.json
{ "security": { "api_token": "your-secret-token", "allow_remote": false } }
Or via environment variable:
MEMORY_API_TOKEN=your-secret-token
When auth is enabled:
- MCP SSE requests must include
Authorization: Bearer - Web UI API endpoints require
?token=or Bearer header - Server binds to
127.0.0.1unlessallow_remote: true - Input validation (title/body size limits) and rate limiting are always active
See CHANGELOG.md for the full list of security features.
Publishing and registries
This repository is prepared for MCP discovery:
- MCP Registry name:
io.github.simoneb79/memory-engine-mcp - Registry metadata:
server.json - Docker/OCI verification label: included in
Dockerfile - Client config example:
mcp.json
See docs/PUBLISHING.md for the publication checklist.
Repository status
- Public GitHub repository: https://github.com/SimoneB79/memory-engine-mcp
- Existing listing: https://mcpmarket.com/server/memory-engine
- License: MIT
License
MIT — see LICENSE.
Made with 🧠 by SimoneB79