mcp-memory-sqlite
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-memory-sqliteRemember that my favorite movie is Inception"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
mcp-memory-sqlite
This repository has been superseded by alexfayers/mcp-memory, a full rewrite in Python. This TypeScript version is no longer maintained.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
Related MCP server: mcp-memory-graph
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-sqliteConfiguration
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.dbMigrate project memory (run from project root):
alexfayers-mcp-memory-sqlite-migrate --source .memory/project.db --project "$(basename "$PWD")" --dest ~/.memory/memory.dbThe 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 devLicense
MIT
Credits
Built with:
better-sqlite3 - Fast SQLite driver
tmcp - MCP server framework
Originally by Scott Spence.
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