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Memento

by iAchilles

Memento

Some memories are best persisted.

Provides persistent memory capabilities through a SQLite-based knowledge graph that stores entities, observations, and relationships with full-text and semantic search using BGE-M3 embeddings for intelligent context retrieval across conversations.

Features

  • Fast keyword search (FTS5)
  • Semantic vector search (sqlite-vec, 1024d)
  • Offline embedding model (bge-m3)
  • Enhanced Relevance Scoring with temporal, popularity, contextual, and importance factors
  • Structured graph of entities, observations, and relations
  • Easy integration with Claude Desktop (via MCP)

Prerequisites

System SQLite Version Check

Memento requires SQLite 3.38+ for FTS5 support. 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:

PlatformInstall command
macOS (Homebrew)brew install sqlite
Debian / Ubuntusudo apt update && sudo apt install sqlite3

Usage

MEMORY_DB_PATH="/Your/Path/To/memory.db" memento ## Starting @iachilles/memento v0.3.3... ## @iachilles/memento v0.3.3 is ready!

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 } } } }

Troubleshooting

sqlite-vec Extension Issues

Important: Memento loads the sqlite-vec extension programmatically through Node.js, NOT through the sqlite3 CLI.

Common misconceptions:

  • ❌ Creating shell aliases for sqlite3 CLI won't affect Memento
  • ❌ Loading extensions in sqlite3 CLI won't help Memento
  • ✅ Use the npm-installed sqlite-vec or set 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

API Overview

This server exposes the following MCP tools:

  • create_entities
  • create_relations
  • add_observations
  • delete_entities
  • delete_relations
  • delete_observations
  • read_graph
  • search_nodes (mode: keyword, semantic)
  • open_nodes
  • set_importance - Set importance level (critical/important/normal/temporary/deprecated)
  • add_tags - Add categorization tags
An example of an instruction set that an LLM should know for effective memory handling (see MEMORY_PROTOCOL.md)

Embedding Model

This project uses @xenova/transformers, with a quantized version of bge-m3, running fully offline in Node.js.

License

MIT

Deploy Server
-
security - not tested
F
license - not found
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quality - not tested

local-only server

The server can only run on the client's local machine because it depends on local resources.

A local, fully-offline MCP memory server that enables persistent storage and retrieval of information using SQLite with both keyword and semantic vector search capabilities.

  1. Features
    1. Prerequisites
      1. System SQLite Version Check
    2. Usage
      1. Troubleshooting
        1. sqlite-vec Extension Issues
      2. API Overview
        1. An example of an instruction set that an LLM should know for effective memory handling (see MEMORY_PROTOCOL.md)
      3. Embedding Model
        1. License

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