Turso▌
by nbbaier
Connect Turso to cloud-based SQLite via LibSQL for SQL data analytics and application development, simplifying content m
Connects to Turso-hosted LibSQL databases, enabling direct SQL query execution against cloud-based SQLite databases for data analysis, content management, and application development workflows.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Developers using Turso for cloud SQLite hosting
- / Data analysis on distributed SQLite databases
- / Content management with edge database queries
capabilities
- / Execute SELECT queries on LibSQL databases
- / Retrieve database table listings
- / View complete database schemas
- / Inspect individual table schemas
what it does
Connects Claude to Turso-hosted LibSQL databases for querying cloud-based SQLite databases. Execute SQL queries and explore database schemas directly from your AI assistant.
about
Turso is a community-built MCP server published by nbbaier that provides AI assistants with tools and capabilities via the Model Context Protocol. Connect Turso to cloud-based SQLite via LibSQL for SQL data analytics and application development, simplifying content m It is categorized under databases.
how to install
You can install Turso 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 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
A Model Context Protocol (MCP) server that provides access to the Turso-hosted LibSQL databases. Currently, the server provides the following functionality:
- Retrieving a list of tables in a database
- Retrieving a database's schema
- Retrieving the schema of a table
- Performing SELECT queries
Configuration
With Claude Desktop
Add this to your claude_desktop_config.json:
{
"mcpServers": [
"turso": {
"command": "npx",
"args": ["-y", "mcp-turso"],
"env": {
"TURSO_DATABASE_URL": "your_url",
"TURSO_AUTH_TOKEN": "your_token"
}
}
]
}
You will need an existing database to continue. If you don't have one, create one. To get the database URL via the Turso CLI, run:
turso db show --url <database-name>
Then get the database authentication token:
turso db tokens create <database-name>
Add those values to your configuration as shown above.
With Cursor
To configure the Turso MCP server with Cursor, add the following to your Cursor settings:
- Open Cursor and go to Settings (⚙️) > Settings (JSON)
- Add the following configuration to your settings JSON:
"mcpServers": {
"turso": {
"command": "npx",
"args": ["-y", "mcp-turso"],
"env": {
"TURSO_DATABASE_URL": "your_url",
"TURSO_AUTH_TOKEN": "your_token"
}
}
}
Replace your_url and your_token with your Turso database URL and authentication token as described in the previous section.
Logging
The server includes a custom logger for debugging outside of Claude Desktop. By default, this logger writes to <parent-dir>/logs/mcp-turso.log, where <parent-dir> is the parent directory of directory containing the mcp-turso script. In other words, if the path to mcp-turso is ~/foo/bin/mcp-turso, the logs will be at ~/foo/logs/mcp-turso.log. If running with NPX as above, the default logs will be:
~/.npm/_npx/<npx-dir-name>/node_modules/mcp-turso/logs/mcp-turso.log
If you would like to specify a custom path, you can include a --logs flag with an absolute posix path in the server's configuration:
{
"mcpServers": [
"turso": {
"command": "npx",
"args": ["-y", "mcp-turso", "--logs", "/Users/<username>/path/to/dir/mcp-logs.log"],
"env": {
"TURSO_DATABASE_URL": "your_url",
"TURSO_AUTH_TOKEN": "your_token"
}
}
]
}
The path to the log file (default or custom) is always logged to stderr when the server is created. For Claude desktop, this will show up in your server logs in ~/Library/Logs/Claude.
Note: Right now, I haven't implemented specifying a custom logging file for Windows, but this is coming.
Server Capabilities
The server provides the following tools:
list_tables- Get a list of all the tables in the database
- No input
- Returns: an array of table names
get_db_schema- Get the schemas of all tables in the database
- No input
- Returns: an array of SQL creation statements
describe_table- View schema information for a specific table
- Input:
table_name(string): Name of table to describe
- Returns: Array of column definitions with names and types
query_database- Execute a SELECT query to read data from the database
- Input:
sql(string): The SELECT SQL query to execute
- Returns: Query results as an object of type
{ columns: string[]; rows: Record<string, unknown>[]; rowCount: number; }
Todo
- Add the ability to specify a custom log file on windows
- Add more query tools
License
MIT License - see the LICENSE file for details.
FAQ
- What is the Turso MCP server?
- Turso 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?
- This profile displays 43 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 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.
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Ratings
4.5★★★★★43 reviews- ★★★★★Dhruvi Jain· Dec 24, 2024
Turso reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Pratham Ware· Dec 20, 2024
According to our notes, Turso benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Ama Zhang· Dec 20, 2024
We evaluated Turso against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Kwame Choi· Dec 4, 2024
Turso is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Mei Thompson· Dec 4, 2024
I recommend Turso for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Sakura Gupta· Nov 23, 2024
Turso is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Noah Shah· Nov 23, 2024
Turso reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Oshnikdeep· Nov 15, 2024
I recommend Turso for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Ama Martinez· Nov 11, 2024
We wired Turso into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Kwame Ramirez· Oct 14, 2024
We evaluated Turso against two servers with overlapping tools; this profile had the clearer scope statement.
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