WhoDB MCP Server
Connect AI assistants to WhoDB, the all-in-one database management tool, for querying and exploring PostgreSQL, MySQL, SQLite, MongoDB, Redis, and more through MCP.
Overview
The WhoDB MCP Server brings database management capabilities to AI assistants, powered by WhoDB's versatile multi-engine architecture. Through the Model Context Protocol, AI models can query, explore, and manage data across WhoDB's supported databases from a single MCP server.
Open Source:
Developed by Clidey with 4,700+ stars on GitHub
Key Features
Multi-Engine Support
Query supported databases from one interface.
Schema Exploration
Browse tables, collections, indexes, and schemas across different database types.
Ad-Hoc Querying
Execute raw SQL or NoSQL queries directly through AI assistant conversations.
Record Management
View, insert, update, and delete records with natural language commands.
Connection Management
Configure multiple database connections and switch between them seamlessly.
Web UI Included
Comes with a built-in web interface alongside the MCP server for visual database management.
Installation
{
"mcpServers": {
"whodb": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-p",
"8080:8080",
"clidey/whodb"
]
}
}
}
Database Connection:
WhoDB's web UI is available at http://localhost:8080. The CLI MCP server is started with whodb mcp serve.
Configuration
WhoDB requires connection configuration for each database engine you want to access. These are configured through the WhoDB web interface:
| Engine | Default Port | Connection String |
|---|---|---|
| PostgreSQL | 5432 | postgresql://user:pass@host:5432/dbname |
| MySQL | 3306 | mysql://user:pass@host:3306/dbname |
| MongoDB | 27017 | mongodb://user:pass@host:27017/dbname |
| Redis | 6379 | redis://user:pass@host:6379 |
| SQLite | — | /path/to/database.db |
Common Use Cases
- Multi-Database AI Assistants: Give AI models access to multiple database engines through a single MCP server integration
- Development & Debugging: Let AI assistants explore database schemas and run diagnostic queries during development
- Data Migration & Analysis: Use AI to write and execute cross-engine queries for data analysis and transformation
- Natural Language Database Management: Query and manage databases without leaving your AI chat interface
Sources
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