DuckDB▌
by ktanaka101
Execute SQL queries and analyze data efficiently in DuckDB databases. Unlock powerful analytics with DuckDB.
Execute SQL queries and analyze data in DuckDB databases.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Data analysts working with local datasets
- / Developers prototyping SQL queries
- / Local data exploration and analysis
- / ETL pipeline development
capabilities
- / Execute SQL queries on DuckDB databases
- / Create and modify database tables
- / Inspect database schemas
- / Analyze local data files
- / Perform joins and aggregations
- / Run data transformations
what it does
Executes SQL queries and analyzes data in DuckDB databases through a single unified query interface. Supports both read-only and read-write modes for local data analysis.
about
DuckDB is a community-built MCP server published by ktanaka101 that provides AI assistants with tools and capabilities via the Model Context Protocol. Execute SQL queries and analyze data efficiently in DuckDB databases. Unlock powerful analytics with DuckDB. It is categorized under databases, analytics data.
how to install
You can install DuckDB 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
DuckDB 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-server-duckdb
A Model Context Protocol (MCP) server implementation for DuckDB, providing database interaction capabilities through MCP tools. It would be interesting to have LLM analyze it. DuckDB is suitable for local analysis.
<a href="https://glama.ai/mcp/servers/fwggl49w22"><img width="380" height="200" src="https://glama.ai/mcp/servers/fwggl49w22/badge" alt="mcp-server-duckdb MCP server" /></a>
Overview
This server enables interaction with a DuckDB database through the Model Context Protocol, allowing for database operations like querying, table creation, and schema inspection.
Components
Resources
Currently, no custom resources are implemented.
Prompts
Currently, no custom prompts are implemented.
Tools
The server implements the following database interaction tool:
- query: Execute any SQL query on the DuckDB database
- Input:
query(string) - Any valid DuckDB SQL statement - Output: Query results as text (or success message for operations like CREATE/INSERT)
- Input:
[!NOTE] The server provides a single unified
queryfunction rather than separate specialized functions, as modern LLMs can generate appropriate SQL for any database operation (SELECT, CREATE TABLE, JOIN, etc.) without requiring separate endpoints.
[!NOTE] When the server is running in
readonlymode, DuckDB's native readonly protection is enforced. This ensures that the Language Model (LLM) cannot perform any write operations (CREATE, INSERT, UPDATE, DELETE), maintaining data integrity and preventing unintended changes.
Configuration
Required Parameters
- db-path (string): Path to the DuckDB database file
- The server will automatically create the database file and parent directories if they don't exist
- If
--readonlyis specified and the database file doesn't exist, the server will fail to start with an error
Optional Parameters
- --readonly: Run server in read-only mode (default:
false)- Description: When this flag is set, the server operates in read-only mode. This means:
- The DuckDB database will be opened with
read_only=True, preventing any write operations. - If the specified database file does not exist, it will not be created.
- Security Benefit: Prevents the Language Model (LLM) from performing any write operations, ensuring that the database remains unaltered.
- The DuckDB database will be opened with
- Reference: For more details on read-only connections in DuckDB, see the DuckDB Python API documentation.
- Description: When this flag is set, the server operates in read-only mode. This means:
- --keep-connection: Re-uses a single DuckDB connection mode (default:
false)- Description: When this flag is set, Re-uses a single DuckDB connection for the entire server lifetime. Enables TEMP objects & slightly faster queries, but can hold an exclusive lock on the file.
Installation
Installing via Smithery
To install DuckDB Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install mcp-server-duckdb --client claude
Claude Desktop Integration
Configure the MCP server in Claude Desktop's configuration file:
MacOS
Location: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows
Location: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"duckdb": {
"command": "uvx",
"args": [
"mcp-server-duckdb",
"--db-path",
"~/mcp-server-duckdb/data/data.db"
]
}
}
}
- Note:
~/mcp-server-duckdb/data/data.dbshould be replaced with the actual path to the DuckDB database file.
Development
Prerequisites
- Python with
uvpackage manager - DuckDB Python package
- MCP server dependencies
Debugging
Debugging MCP servers can be challenging due to their stdio-based communication. We recommend using the MCP Inspector for the best debugging experience.
Using MCP Inspector
- Install the inspector using npm:
npx @modelcontextprotocol/inspector uv --directory ~/codes/mcp-server-duckdb run mcp-server-duckdb --db-path ~/mcp-server-duckdb/data/data.db
- Open the provided URL in your browser to access the debugging interface
The inspector provides visibility into:
- Request/response communication
- Tool execution
- Server state
- Error messages
FAQ
- What is the DuckDB MCP server?
- DuckDB 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 DuckDB?
- This profile displays 40 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.
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Ratings
4.6★★★★★40 reviews- ★★★★★Kaira Perez· Dec 20, 2024
DuckDB is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Nia Farah· Dec 8, 2024
Strong directory entry: DuckDB surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Alexander Srinivasan· Dec 4, 2024
DuckDB has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Carlos Gill· Nov 27, 2024
I recommend DuckDB for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Alexander Iyer· Nov 23, 2024
According to our notes, DuckDB benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Carlos Agarwal· Nov 11, 2024
DuckDB is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Carlos Bansal· Oct 18, 2024
We evaluated DuckDB against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Alexander Gill· Oct 14, 2024
DuckDB is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Sofia Agarwal· Oct 2, 2024
According to our notes, DuckDB benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Valentina Kapoor· Sep 25, 2024
DuckDB reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
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