by iachilles
Memento enables persistent memory with a SQLite-based knowledge graph for intelligent context retrieval using advanced B
Creates persistent memory for AI conversations using a SQLite knowledge graph that stores entities, observations, and relationships with semantic search capabilities.
Memento is a community-built MCP server published by iachilles that provides AI assistants with tools and capabilities via the Model Context Protocol. Memento enables persistent memory with a SQLite-based knowledge graph for intelligent context retrieval using advanced B It is categorized under ai ml.
You can install Memento in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Memento is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
According to our notes, Memento benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
I recommend Memento for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Memento is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Memento is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Memento has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Strong directory entry: Memento surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Memento is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Useful MCP listing: Memento is the kind of server we cite when onboarding engineers to host + tool permissions.
Memento has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Strong directory entry: Memento surfaces stars and publisher context so we could sanity-check maintenance before adopting.
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Some memories are best persisted.
Provides persistent memory capabilities through a SQLite-based knowledge graph that stores entities, observations, and relationships with semantic search using BGE-M3 embeddings for intelligent context retrieval across conversations.
bge-m3)entities, observations, and relationsMemento requires SQLite 3.38+. Most macOS and Linux distros ship sqlite3 out of the box, but double-check that it's there and new enough:
sqlite3 --version # should print a version string, e.g. 3.46.0
Important Note: This check is just to verify SQLite is installed on your system. Memento does NOT use the sqlite3 CLI for its operation it uses the Node.js sqlite3 module internally.
If you see "command not found" (or your version is older than 3.38), install SQLite:
| Platform | Install command |
|---|---|
| macOS (Homebrew) | brew install sqlite |
| Debian / Ubuntu | sudo apt update && sudo apt install sqlite3 |
Memento now supports pluggable storage backends. Configuration is controlled entirely through environment variables so it remains easy to embed inside MCP workflows.
| Variable | Description |
|---|---|
MEMORY_DB_DRIVER | Optional selector for the database backend. Defaults to sqlite. Set to postgres to enable the PostgreSQL manager. |
MEMORY_DB_PATH | Filesystem path for the SQLite database file (only used when the driver is sqlite). |
SQLITE_VEC_PATH | Optional absolute path to a pre-built sqlite-vec extension shared library. |
MEMORY_DB_DSN / DATABASE_URL | PostgreSQL connection string consumed by the pg client. |
PGHOST, PGPORT, PGUSER, PGPASSWORD, PGDATABASE | Individual PostgreSQL connection parameters. Used when no DSN is provided. |
PGSSLMODE | When set to require, SSL will be enabled with rejectUnauthorized: false. |
pgvector
extension. It is automatically initialized with CREATE EXTENSION IF NOT EXISTS vector.Claude Desktop:
{
"mcpServers": {
"memory": {
"description": "Custom memory backed by SQLite + vec + FTS5",
"command": "npx",
"args": [
"@iachilles/memento@latest"
],
"env": {
"MEMORY_DB_PATH": "/Path/To/Your/memory.db"
},
"options": {
"autoStart": true,
"restartOnCrash": true
}
}
}
}
Important: Memento loads the sqlite-vec extension programmatically through Node.js, NOT through the sqlite3 CLI.
Common misconceptions:
SQLITE_VEC_PATH environment variable if automatic detection fails. This should point to the Node.js-compatible version of the extension, typically found in your node_modules directory.If automatic vec loading fails:
# Find the Node.js-compatible vec extension
find node_modules -name "vec0.dylib" # macOS
find node_modules -name "vec0.so" # Linux
# Use it via environment variable
SQLITE_VEC_PATH="/full/path/to/node_modules/sqlite-vec-darwin-x64/vec0.dylib" memento
This server exposes the following MCP tools:
create_entitiescreate_relationsadd_observationsdelete_entitiesdelete_relationsdelete_observationsread_graphsearch_nodesopen_nodesset_importance - Set importance level (critical/important/normal/temporary/deprecated)This project uses @xenova/transformers, with a quantized version of bge-m3, running fully offline in Node.js.
MIT
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.