About Database Schema MCP Server
Database Schema MCP Server exposes database structure for developers and AI clients inspecting PostgreSQL, MySQL, or SQLite databases. It provides both table-level details and a complete schema view, including views and indexes.
Key features
- 01Connect to PostgreSQL, MySQL, and SQLite
- 02List database tables
- 03Inspect individual table schemas
- 04Retrieve schemas with tables, views, and indexes
Use cases
- 01Check available tables in a database
- 02Inspect a table before querying it
- 03Review a database's full structure
MCP support
It provides MCP tools for connecting to databases and retrieving table lists and schema details for MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEDatabase Schema MCP Server
A powerful MCP server that provides tools to read and expose database schemas from various database types (PostgreSQL, MySQL, SQLite, etc.).
🌟 Features
- Connect to different types of databases
- List all tables in a database
- Get detailed schema information for specific tables
- Get complete database schema including tables, views, and indexes
- Support for multiple database types (PostgreSQL, MySQL, SQLite)
🚀 Installation
Prerequisites
- Python 3.x
- Virtual environment (recommended)
Basic Installation
- Create and activate a virtual environment:
# Create virtual environment
python -m venv venv
# Activate virtual environment
# On Unix/macOS:
source venv/bin/activate
# On Windows:
venv\Scripts\activate
- Install dependencies:
pip install -r requirements.txt
Windows MCP Installation
-
Install Node.js:
- Download and install from Node.js official website
- Verify installation by running
node --versionin PowerShell
-
Update System Path:
$env:Path = [System.Environment]::GetEnvironmentVariable("Path","Machine") + ";" + [System.Environment]::GetEnvironmentVariable("Path","User")
-
If Node.js is not recognized, manually add to Path:
- Press
Windows + R - Type
sysdm.cpland press Enter - Go to "Advanced" tab
- Click "Environment Variables"
- Under "System variables", find and select "Path"
- Click "Edit"
- Add
C:\Program Files\nodejs\if not present - Click "OK" on all windows
- Restart your computer
- Press
-
Install MCP:
- Download the
mcp-install.ps1script - Unblock the file (right-click → Properties → Unblock)
- Open PowerShell as Administrator and run:
Set-ExecutionPolicy unrestricted - Navigate to script location and run:
.\mcp-install.ps1 @modelcontextprotocol/server-postgres - Exit Claude Desktop completely (check system tray)
- Configure server in
C:\Users\YOUR_USERNAME\AppData\Roaming\Claude\claude_desktop_config.json - Copy MCP server config to
mcp.jsonin Cursor - Restart Cursor
- Download the
MCP Configuration Example
Create a .cursor/mcp.json file in your project root with the following structure:
{
"mcpServers": {
"local-db": {
"args": [
"C:\\Users\\YOUR_USERNAME\\AppData\\Roaming\\npm\\node_modules\\@modelcontextprotocol\\server-postgres\\dist\\index.js",
"database-url"
],
"command": "node"
},
"staging-db": {
"args": [
"C:\\Users\\YOUR_USERNAME\\AppData\\Roaming\\npm\\node_modules\\@modelcontextprotocol\\server-postgres\\dist\\index.js",
"database-url"
],
"command": "node"
},
"production-db": {
"args": [
"C:\\Users\\YOUR_USERNAME\\AppData\\Roaming\\npm\\node_modules\\@modelcontextprotocol\\server-postgres\\dist\\index.js",
"database-url"
],
"command": "node"
}
}
}
Replace YOUR_USERNAME with your Windows username and ensure the paths match your Node.js module installation location.
💻 Usage
Starting the Server
python src/server.py
Available Tools
1. Connect to Database
config = {
"type": "postgresql", # or "mysql", "sqlite"
"host": "localhost",
"port": 5432,
"database": "mydb",
"username": "user",
"password": "password"
}
result = await connect_database(config)
2. List Tables
tables = await list_tables("postgresql://user:password@localhost:5432/mydb")
3. Get Table Schema
schema = await get_table_schema("postgresql://user:password@localhost:5432/mydb", "users")
4. Get Database Schema
schema = await get_database_schema("postgresql://user:password@localhost:5432/mydb")
📚 Example Usage with Claude
# Connect to a database
config = {
"type": "postgresql",
"host": "localhost",
"port": 5432,
"database": "mydb",
"username": "user",
"password": "password"
}
await connect_database(config)
# Get the complete schema
schema = await get_database_schema("postgresql://user:password@localhost:5432/mydb")
# Analyze the schema
print(f"Database has {len(schema['tables'])} tables")
for table_name, table_info in schema['tables'].items():
print(f"\nTable: {table_name}")
print(f"Columns: {len(table_info['columns'])}")
print(f"Primary Keys: {table_info['primary_keys']}")
print(f"Foreign Keys: {len(table_info['foreign_keys'])}")
🔒 Security Best Practices
- Never expose sensitive database credentials in client-side code
- Use environment variables or secure configuration management for credentials
- Implement proper access controls and authentication
- Use SSL/TLS for database connections when possible
Comments
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