Turso SQLite▌
by spences10
Turso SQLite connects AI assistants to Turso SQLite databases, offering organization management, queries, and advanced v
Provides a bridge between AI assistants and Turso SQLite databases, enabling organization-level management and database-level queries with persistent context, schema exploration, and vector similarity search capabilities.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / AI-powered database administration and monitoring
- / LLM applications requiring SQLite database access
- / Teams managing multiple Turso databases
- / Applications with vector search requirements
capabilities
- / List and manage databases in Turso organizations
- / Execute read-only SQL queries (SELECT, PRAGMA)
- / Run destructive SQL operations (INSERT, UPDATE, DELETE)
- / Explore database schemas and table structures
- / Perform vector similarity searches
- / Generate database authentication tokens
what it does
Connects AI assistants to Turso SQLite databases with organization management and secure query execution. Separates read-only operations from destructive queries for safety.
about
Turso SQLite is a community-built MCP server published by spences10 that provides AI assistants with tools and capabilities via the Model Context Protocol. Turso SQLite connects AI assistants to Turso SQLite databases, offering organization management, queries, and advanced v It is categorized under databases, ai ml.
how to install
You can install Turso SQLite 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
Turso SQLite 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-turso-cloud
A Model Context Protocol (MCP) server that provides integration with Turso databases for LLMs. This server implements a two-level authentication system to handle both organization-level and database-level operations, making it easy to manage and query Turso databases directly from LLMs.
<a href="https://glama.ai/mcp/servers/hnkzlqoh92"> <img width="380" height="200" src="https://glama.ai/mcp/servers/hnkzlqoh92/badge" alt="mcp-turso-cloud MCP server" /> </a>Features
🏢 Organization-Level Operations
- List Databases: View all databases in your Turso organization
- Create Database: Create new databases with customizable options
- Delete Database: Remove databases from your organization
- Generate Database Token: Create authentication tokens for specific databases
💾 Database-Level Operations
- List Tables: View all tables in a specific database
- Execute Read-Only Query: Run SELECT and PRAGMA queries (read-only operations)
- Execute Query: Run potentially destructive SQL queries (INSERT, UPDATE, DELETE, etc.)
- Describe Table: Get schema information for database tables
- Vector Search: Perform vector similarity search using SQLite vector extensions
⚠️ IMPORTANT: Query Execution Security ⚠️
This server implements a security-focused separation between read-only and destructive database operations:
- Use
execute_read_only_queryfor SELECT and PRAGMA queries (safe, read-only operations) - Use
execute_queryfor INSERT, UPDATE, DELETE, CREATE, DROP, and other operations that modify data
This separation allows for different permission levels and approval requirements:
- Read-only operations can be auto-approved in many contexts
- Destructive operations can require explicit approval for safety
ALWAYS CAREFULLY READ AND REVIEW SQL QUERIES BEFORE APPROVING THEM! This is especially critical for destructive operations that can modify or delete data. Take time to understand what each query does before allowing it to execute.
Two-Level Authentication System
The server implements a sophisticated authentication system:
-
Organization-Level Authentication
- Uses a Turso Platform API token
- Manages databases and organization-level operations
- Obtained through the Turso dashboard
-
Database-Level Authentication
- Uses database-specific tokens
- Generated automatically using the organization token
- Cached for performance and rotated as needed
Configuration
This server requires configuration through your MCP client. Here are examples for different environments:
Cline/Claude Desktop Configuration
Add this to your Cline/Claude Desktop MCP settings:
{
"mcpServers": {
"mcp-turso-cloud": {
"command": "npx",
"args": ["-y", "mcp-turso-cloud"],
"env": {
"TURSO_API_TOKEN": "your-turso-api-token",
"TURSO_ORGANIZATION": "your-organization-name",
"TURSO_DEFAULT_DATABASE": "optional-default-database"
}
}
}
}
Claude Desktop with WSL Configuration
For WSL environments, add this to your Claude Desktop configuration:
{
"mcpServers": {
"mcp-turso-cloud": {
"command": "wsl.exe",
"args": [
"bash",
"-c",
"TURSO_API_TOKEN=your-token TURSO_ORGANIZATION=your-org node /path/to/mcp-turso-cloud/dist/index.js"
]
}
}
}
Environment Variables
The server requires the following environment variables:
TURSO_API_TOKEN: Your Turso Platform API token (required)TURSO_ORGANIZATION: Your Turso organization name (required)TURSO_DEFAULT_DATABASE: Default database to use when none is specified (optional)TOKEN_EXPIRATION: Expiration time for generated database tokens (optional, default: '7d')TOKEN_PERMISSION: Permission level for generated tokens (optional, default: 'full-access')
API
The server implements MCP Tools organized by category:
Organization Tools
list_databases
Lists all databases in your Turso organization.
Parameters: None
Example response:
{
"databases": [
{
"name": "customer_db",
"id": "abc123",
"region": "us-east",
"created_at": "2023-01-15T12:00:00Z"
},
{
"name": "product_db",
"id": "def456",
"region": "eu-west",
"created_at": "2023-02-20T15:30:00Z"
}
]
}
create_database
Creates a new database in your organization.
Parameters:
name(string, required): Name for the new databasegroup(string, optional): Group to assign the database toregions(string[], optional): Regions to deploy the database to
Example:
{
"name": "analytics_db",
"group": "production",
"regions": ["us-east", "eu-west"]
}
delete_database
Deletes a database from your organization.
Parameters:
name(string, required): Name of the database to delete
Example:
{
"name": "test_db"
}
generate_database_token
Generates a new token for a specific database.
Parameters:
database(string, required): Database nameexpiration(string, optional): Token expiration timepermission(string, optional): Permission level ('full-access' or 'read-only')
Example:
{
"database": "customer_db",
"expiration": "30d",
"permission": "read-only"
}
Database Tools
list_tables
Lists all tables in a database.
Parameters:
database(string, optional): Database name (uses context if not provided)
Example:
{
"database": "customer_db"
}
execute_read_only_query
Executes a read-only SQL query (SELECT, PRAGMA) against a database.
Parameters:
query(string, required): SQL query to execute (must be SELECT or PRAGMA)params(object, optional): Query parametersdatabase(string, optional): Database name (uses context if not provided)
Example:
{
"query": "SELECT * FROM users WHERE age > ?",
"params": { "1": 21 },
"database": "customer_db"
}
execute_query
Executes a potentially destructive SQL query (INSERT, UPDATE, DELETE, CREATE, etc.) against a database.
Parameters:
query(string, required): SQL query to execute (cannot be SELECT or PRAGMA)params(object, optional): Query parametersdatabase(string, optional): Database name (uses context if not provided)
Example:
{
"query": "INSERT INTO users (name, age) VALUES (?, ?)",
"params": { "1": "Alice", "2": 30 },
"database": "customer_db"
}
describe_table
Gets schema information for a table.
Parameters:
table(string, required): Table namedatabase(string, optional): Database name (uses context if not provided)
Example:
{
"table": "users",
"database": "customer_db"
}
vector_search
Performs vector similarity search using SQLite vector extensions.
Parameters:
table(string, required): Table namevector_column(string, required): Column containing vectorsquery_vector(number[], required): Query vector for similarity searchlimit(number, optional): Maximum number of results (default: 10)database(string, optional): Database name (uses context if not provided)
Example:
{
"table": "embeddings",
"vector_column": "embedding",
"query_vector": [0.1, 0.2, 0.3, 0.4],
"limit": 5,
"database": "vector_db"
}
Development
Setup
- Clone the repository
- Install dependencies:
npm install
- Build the project:
npm run build
- Run in development mode:
npm run dev
Publishing
- Update version in package.json
- Build the project:
npm run build
- Publish to npm:
npm publish
Troubleshooting
API Token Issues
If you encounter authentication errors:
- Verify your Turso API token is valid and has the necessary permissions
- Check that your organization name is correct
- Ensure your token hasn't expired
Database Connection Issues
If you have trouble connecting to databases:
- Verify the database exists in your organization
- Check that your API token has access to the database
- Ensure the database name is spelled correctly
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
MIT License - see the LICENSE file for details.
Acknowledgments
Built on:
FAQ
- What is the Turso SQLite MCP server?
- Turso SQLite is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Turso SQLite?
- This profile displays 57 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Direct Database Queries from AI
Enable Claude to query your database directly using natural language
Example
Ask 'Show me top 10 customers by revenue this month' and get SQL results instantly
Eliminate manual SQL writing for ad-hoc queries, get insights 10x faster
Data Analysis & Reporting
Generate complex reports and analytics without leaving conversation
Example
Analyze sales trends, cohort retention, user behavior patterns conversationally
Democratize data access—non-technical team members can query databases
Schema Exploration
Understand database structure, relationships, and data models
Example
'Explain the user_orders table schema and its relationships'
Onboard engineers faster, explore unfamiliar databases efficiently
Data Validation & Quality Checks
Run data quality queries to catch anomalies and inconsistencies
Example
Find duplicate records, missing values, orphaned foreign keys automatically
Maintain data integrity with less manual SQL work
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor with MCP support
- ›Database credentials (read-only recommended for safety)
- ›Network access from Claude client to database
- ›Understanding of database security and access control
Time Estimate
15-30 minutes including configuration and testing
Installation Steps
- 1.Install MCP server: npm install -g @modelcontextprotocol/server-[name]
- 2.Configure database connection in Claude Desktop config (~/.claude/mcp.json)
- 3.Provide connection string: host, port, database, username, password
- 4.Restart Claude Desktop to load MCP server
- 5.Test connection: 'List all tables in database'
- 6.Run simple query: 'Show me 5 rows from users table'
- 7.Verify results and permissions are correct
- 8.Document query patterns for team use
Troubleshooting
- ⚠Connection refused: Check database is running and network accessible
- ⚠Authentication failed: Verify credentials, check user permissions
- ⚠Claude can't see tables: Grant appropriate read permissions to database user
- ⚠Slow queries: Add indexes, limit result set size, use read replicas
- ⚠MCP server not loading: Check config syntax, restart Claude Desktop
Best Practices▌
✓ Do
- +Use read-only database credentials to prevent accidental writes
- +Connect to read replica, not production primary database
- +Set query timeout limits to prevent long-running queries
- +Document database schema and common queries for AI context
- +Monitor query performance and optimize slow queries
- +Use connection pooling for better performance
- +Test with non-production data first
✗ Don't
- −Don't use production write credentials—risk of data corruption
- −Don't query production database during peak traffic hours
- −Don't expose sensitive PII without proper access controls
- −Don't skip query result validation—AI can misinterpret schema
- −Don't allow unlimited result set sizes—set LIMIT clauses
- −Don't share database credentials in plain text config files
💡 Pro Tips
- ★Create database views for common queries to simplify AI access
- ★Add schema comments/descriptions so AI understands column meanings
- ★Use semantic table/column names ('customer_lifetime_value' not 'clv')
- ★Set up query logging to audit what Claude is querying
- ★Create saved query templates for recurring analysis
- ★Combine with data visualization tools for better insights
Technical Details▌
Architecture
MCP server acts as bridge between Claude and database, translating natural language to SQL queries and returning results in structured format.
Protocols
- Model Context Protocol (MCP)
- Database-specific protocols (PostgreSQL, MySQL, MongoDB)
Compatibility
- PostgreSQL
- MySQL
- SQLite
- MongoDB
- Redis
When to Use This▌
✓ Use When
Use for ad-hoc data queries, exploratory analysis, report generation, schema exploration, and democratizing data access. Best for read-heavy analytics workloads.
✗ Avoid When
Avoid for production write operations, mission-critical transactions, real-time OLTP workloads, or when database contains sensitive PII without proper access controls. Use read replicas, not primary.
Integration▌
- →Read replica connection for analytics queries
- →Database view layer to abstract complex joins
- →Query result caching for repeated questions
- →Audit logging of all AI-generated queries
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
List & Promote Your MCP Server
Share your MCP server with the developer community
Ratings
4.6★★★★★57 reviews- ★★★★★Diego Torres· Dec 24, 2024
Turso SQLite is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Ama Abebe· Dec 8, 2024
Turso SQLite has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Chinedu Agarwal· Dec 8, 2024
Turso SQLite reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Shikha Mishra· Dec 4, 2024
Turso SQLite is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Chinedu Bansal· Nov 27, 2024
According to our notes, Turso SQLite benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Ama Okafor· Nov 27, 2024
Useful MCP listing: Turso SQLite is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Yash Thakker· Nov 23, 2024
Strong directory entry: Turso SQLite surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Sakshi Patil· Nov 15, 2024
We evaluated Turso SQLite against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Sakura Flores· Nov 15, 2024
I recommend Turso SQLite for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Diego Ramirez· Oct 18, 2024
I recommend Turso SQLite for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
showing 1-10 of 57