LibSQL Memory▌

by spences10
LibSQL Memory offers a persistent memory database using LibSQL to store and retrieve knowledge graph entities and relati
Provides a LibSQL-based persistent memory database for storing and retrieving knowledge graph entities and relations across conversations.
best for
- / AI assistants that need long-term memory
- / Building persistent knowledge bases from conversations
- / LLM applications requiring context continuity
- / Knowledge graph management for AI systems
capabilities
- / Store entities and relationships in knowledge graphs
- / Search stored knowledge with fuzzy text matching
- / Persist memory across conversation sessions
- / Connect to local SQLite or remote LibSQL databases
- / Rank search results by relevance
- / Manage knowledge graph relationships
what it does
Provides a persistent LibSQL database for storing knowledge graph entities and relationships that persist across AI conversations. Enables AI assistants to remember and build upon previous interactions.
about
LibSQL Memory is a community-built MCP server published by spences10 that provides AI assistants with tools and capabilities via the Model Context Protocol. LibSQL Memory offers a persistent memory database using LibSQL to store and retrieve knowledge graph entities and relati It is categorized under ai ml, databases.
how to install
You can install LibSQL Memory 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.
license
MIT
LibSQL Memory is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
mcp-memory-libsql
A high-performance, persistent memory system for the Model Context Protocol (MCP) powered by libSQL with optimized text search for LLM context efficiency.
<a href="https://glama.ai/mcp/servers/22lg4lq768"> <img width="380" height="200" src="https://glama.ai/mcp/servers/22lg4lq768/badge" alt="Glama badge" /> </a>Features
- 🚀 High-performance text search with relevance ranking
- 💾 Persistent storage of entities and relations
- 🔍 Flexible text search with fuzzy matching
- 🎯 Context-optimized for LLM efficiency
- 🔄 Knowledge graph management
- 🌐 Compatible with local and remote libSQL databases
- 🔒 Secure token-based authentication for remote databases
Configuration
This server is designed to be used as part of an MCP configuration. Here are examples for different environments:
Cline Configuration
Add this to your Cline MCP settings:
{
"mcpServers": {
"mcp-memory-libsql": {
"command": "npx",
"args": ["-y", "mcp-memory-libsql"],
"env": {
"LIBSQL_URL": "file:/path/to/your/database.db"
}
}
}
}
Claude Desktop with WSL Configuration
For a detailed guide on setting up this server with Claude Desktop in WSL, see Getting MCP Server Working with Claude Desktop in WSL.
Add this to your Claude Desktop configuration for WSL environments:
{
"mcpServers": {
"mcp-memory-libsql": {
"command": "wsl.exe",
"args": [
"bash",
"-c",
"source ~/.nvm/nvm.sh && LIBSQL_URL=file:/path/to/database.db /home/username/.nvm/versions/node/v20.12.1/bin/npx mcp-memory-libsql"
]
}
}
}
Database Configuration
The server supports both local SQLite and remote libSQL databases through the LIBSQL_URL environment variable:
For local SQLite databases:
{
"env": {
"LIBSQL_URL": "file:/path/to/database.db"
}
}
For remote libSQL databases (e.g., Turso):
{
"env": {
"LIBSQL_URL": "libsql://your-database.turso.io",
"LIBSQL_AUTH_TOKEN": "your-auth-token"
}
}
Note: When using WSL, ensure the database path uses the Linux
filesystem format (e.g., /home/username/...) rather than Windows
format.
By default, if no URL is provided, it will use file:/memory-tool.db
in the current directory.
API
The server implements the standard MCP memory interface with optimized text search:
- Entity Management
- Create/Update entities with observations
- Delete entities
- Search entities by text with relevance ranking
- Explore entity relationships
- Relation Management
- Create relations between entities
- Delete relations
- Query related entities
Architecture
The server uses a libSQL database with the following schema:
- Entities table: Stores entity information with timestamps
- Observations table: Stores entity observations
- Relations table: Stores relationships between entities
- Text search with relevance ranking (name > type > observation)
Development
Publishing
Due to npm 2FA requirements, publishing needs to be done manually:
- Create a changeset (documents your changes):
pnpm changeset
- Version the package (updates version and CHANGELOG):
pnpm changeset version
- Publish to npm (will prompt for 2FA code):
pnpm release
Contributing
Contributions are welcome! Please read our contributing guidelines before submitting pull requests.
License
MIT License - see the LICENSE file for details.
Acknowledgments
- Built on the Model Context Protocol
- Powered by libSQL