Memory Sqlite
БесплатноНе проверенA personal knowledge graph and memory system for AI assistants using SQLite with FTS5 full-text search, enabling persistent memory across conversations with Cla
Описание
A personal knowledge graph and memory system for AI assistants using SQLite with FTS5 full-text search, enabling persistent memory across conversations with Claude or any MCP-compatible AI.
README
This repository has been superseded by alexfayers/mcp-memory, a full rewrite in Python. This TypeScript version is no longer maintained.
A personal knowledge graph and memory system for AI assistants using SQLite with FTS5 full-text search. Perfect for giving Claude (or any MCP-compatible AI) persistent memory across conversations!
Fork of spences10/mcp-memory-sqlite with additional tools and FTS5 search upgrade.
Why Use This?
Give your AI assistant a memory! This tool lets Claude (or other AI assistants) remember entities, concepts, and their relationships across conversations. Perfect for:
- 📚 Personal Knowledge Management - Build your own knowledge graph
- 🤖 AI Assistant Memory - Help Claude remember important information about your projects, preferences, and context
- 🔗 Relationship Tracking - Connect ideas, people, projects, and concepts
- 🔍 Smart Text Search - Find information using FTS5 full-text search with BM25 relevance ranking
Features
- 100% Local & Private: All your data stays on your machine
- Easy Setup: Works out-of-the-box with Claude Desktop
- FTS5 Full-Text Search: Multi-word queries with BM25 relevance ranking
- Smart Deduplication: Automatically prevents duplicate relationships
- Context-Optimized: Designed specifically for LLM context efficiency
- Safe Observation Updates: Append or delete individual observations without overwriting
- Graph Traversal: Explore 1-hop entity relationships filtered by type
Quick Start
For Claude Desktop users (recommended):
Add this to your Claude Desktop config:
{
"mcpServers": {
"memory": {
"command": "npx",
"args": ["-y", "mcp-memory-sqlite"]
}
}
}
That's it! Claude can now remember things across conversations.
Installation
If you want to use it in your own project:
npm install mcp-memory-sqlite
# or
pnpm add mcp-memory-sqlite
Configuration
Optional: Customize the database location with an environment variable:
SQLITE_DB_PATH: Where to store your data (default:./sqlite-memory.db)
MCP Tools
create_entities
Create or update entities with observations. Note: This overwrites
all existing observations for an entity - use add_observations to
append instead.
Parameters:
entities: Array of entity objectsname(string): Unique entity identifierentityType(string): Type/category of the entityobservations(string[]): Array of observation strings
Example:
{
"entities": [
{
"name": "Claude",
"entityType": "AI Assistant",
"observations": [
"Created by Anthropic",
"Focuses on being helpful, harmless, and honest"
]
}
]
}
add_observations
Append observations to an existing entity without overwriting existing ones. Skips duplicate observations. Throws if the entity does not exist.
Parameters:
entityName(string): Name of the entity to updateobservations(string[]): Observations to add
Example:
{
"entityName": "Claude",
"observations": ["Supports extended thinking mode"]
}
delete_observations
Delete specific observations from an existing entity by content match. Returns the count of deleted observations. Throws if the entity does not exist.
Parameters:
entityName(string): Name of the entity to updateobservations(string[]): Exact observation strings to delete
Example:
{
"entityName": "Claude",
"observations": ["Focuses on being helpful, harmless, and honest"]
}
search_nodes
Search for entities and their relations using FTS5 full-text search with BM25 relevance ranking. Multi-word queries match terms independently across entity names, types, and all observations.
Parameters:
query(string): Text to search forlimit(number, optional): Maximum results to return (default: 10, max: 50)
Example:
{
"query": "AI Assistant",
"limit": 5
}
read_graph
Get recent entities and their relations (returns last 10 entities by default).
Parameters: None
create_relations
Create relationships between entities. Duplicate relations (same source, target, and type) are automatically ignored.
Parameters:
relations: Array of relation objectssource(string): Source entity nametarget(string): Target entity nametype(string): Relationship type
Example:
{
"relations": [
{
"source": "Claude",
"target": "Anthropic",
"type": "created_by"
}
]
}
get_entity_with_relations
Get an entity along with all its relations and directly connected entities.
Parameters:
name(string): Entity name to retrieve
Example:
{
"name": "Claude"
}
search_related_nodes
Get an entity along with all its directly related entities. Optionally filter by entity type and/or relation type for targeted graph traversal.
Parameters:
name(string): Entity name to retrieveentityType(string, optional): Filter related entities by typerelationType(string, optional): Filter relations by type
Example:
{
"name": "my-project",
"entityType": "task",
"relationType": "implements"
}
delete_entity
Delete an entity and all associated data (observations and relations).
Parameters:
name(string): Entity name to delete
delete_relation
Delete a specific relation between entities.
Parameters:
source(string): Source entity nametarget(string): Target entity nametype(string): Relationship type
Usage with Claude Desktop
Add to your Claude Desktop configuration:
Minimal configuration (uses default ./sqlite-memory.db):
{
"mcpServers": {
"memory": {
"command": "npx",
"args": ["-y", "mcp-memory-sqlite"]
}
}
}
With custom database path:
{
"mcpServers": {
"memory": {
"command": "npx",
"args": ["-y", "mcp-memory-sqlite"],
"env": {
"SQLITE_DB_PATH": "/path/to/your/memory.db"
}
}
}
}
Database Schema
Tables
- entities: Stores entity metadata (name, type, creation time)
- observations: Stores observations linked to entities
- relations: Stores relationships between entities
- schema_version: Tracks applied migrations
- entities_fts: FTS5 virtual table for full-text search (with sync triggers)
Migrating from Old Single-Project Databases
If you have existing single-project memory databases (e.g., global.db, project.db), use the alexfayers-mcp-memory-sqlite-migrate tool to import them into the new unified multi-project database:
Migrate global memory:
alexfayers-mcp-memory-sqlite-migrate --source ~/.memory/global.db --project global --dest ~/.memory/memory.db
Migrate project memory (run from project root):
alexfayers-mcp-memory-sqlite-migrate --source .memory/project.db --project "$(basename "$PWD")" --dest ~/.memory/memory.db
The tool will:
- Create the destination DB if it doesn't exist
- Run all schema migrations automatically
- Import entities with their observations
- Import relations between entities
- Skip entities with no observations
- Deduplicate observations that already exist
Development
# Install dependencies
pnpm install
# Build
pnpm run build
# Run in development mode
pnpm run dev
License
MIT
Credits
Built with:
- better-sqlite3 - Fast SQLite driver
- tmcp - MCP server framework
Originally by Scott Spence.
Установка Memory Sqlite
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/alexfayers/mcp-memory-sqliteFAQ
Memory Sqlite MCP бесплатный?
Да, Memory Sqlite MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Memory Sqlite?
Нет, Memory Sqlite работает без API-ключей и переменных окружения.
Memory Sqlite — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Memory Sqlite в Claude Desktop, Claude Code или Cursor?
Открой Memory Sqlite на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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