---
name: database-mcp
description: MCP server for SQL databases. Connect AI agents to PostgreSQL, MySQL, MariaDB, and SQLite for natural language
  queries, schema management, and data operations.
domain: integrations
tags:
- ai-agent
- api
- database
- integrations
- mcp
- third-party
---

# Database MCP Skill

## When NOT to Use

- Task is outside your authorization scope
- You need to implement controls (use implementing-* skills)
- Task is about analysis, not action (use analyzing-* skills)
- You don't have access to target systems
- Task requires compliance expertise (consult professionals)
- Task is about defense, not offense (use defensive skills)


## Overview

MCP server for SQL databases enabling AI agents to interact with PostgreSQL, MySQL, MariaDB, and SQLite through natural language. Provides 12+ MCP tools for query execution, schema inspection, and database management.

**Source**: [guyinwonder168/database-mcp](https://github.com/guyinwonder168)  
**Supported**: PostgreSQL, MySQL, MariaDB, SQLite  
**Tools**: 12+ MCP tools

---

## When to Use

- Query databases with natural language
- Inspect and explore database schemas
- Generate SQL queries
- Analyze database performance
- Manage database migrations
- Data analysis and reporting

---

## MCP Setup
```json
{
  "enabled": true,
  "autoRun": false,
  "timeout": 30000,
  "retries": 3
}
```

Set environment variables as needed for authentication and endpoints.


### Installation
```json
{
  "mcpServers": {
    "database": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-sql"],
      "env": {
        "DATABASE_URL": "${DATABASE_URL}"
      }
    }
  }
}
```

### PostgreSQL (Anthropic Official)
```json
{
  "mcpServers": {
    "postgres": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-postgres"],
      "env": {
        "DATABASE_URL": "postgresql://user:pass@host/db"
      }
    }
  }
}
```

---

## Available Tools
| Tool | Purpose | Required |
|------|---------|----------|
| CLI | Primary execution | Yes |
| API client | External service calls | Conditional |
| Validator | Output checking | Recommended |


### 1. Query Execution
```typescript
// Execute SQL query
executeQuery({
  sql: "SELECT * FROM users WHERE created_at > NOW() - INTERVAL '7 days'",
  database: "production"
})
```

### 2. Schema Inspection
```typescript
// Get table schema
getSchema({
  table: "users",
  database: "production"
})
```

### 3. List Tables
```typescript
// List all tables
listTables({
  database: "production",
  schema: "public"
})
```

### 4. Query Analysis
```typescript
// Analyze query performance
explainQuery({
  sql: "SELECT * FROM orders WHERE status = 'pending'",
  database: "production"
})
```

### 5. Create Table
```typescript
// Create new table
createTable({
  name: "products",
  columns: [
    { name: "id", type: "SERIAL PRIMARY KEY" },
    { name: "name", type: "VARCHAR(255)" },
    { name: "price", type: "DECIMAL(10,2)" }
  ],
  database: "production"
})
```

### 6. Insert Data
```typescript
// Insert rows
insert({
  table: "users",
  data: { name: "John", email: "john@example.com" },
  database: "production"
})
```

### 7. Update Data
```typescript
// Update rows
update({
  table: "users",
  data: { status: "active" },
  where: "id = 1",
  database: "production"
})
```

### 8. Delete Data
```typescript
// Delete rows
delete({
  table: "users",
  where: "status = 'inactive' AND created_at < NOW() - INTERVAL '1 year'",
  database: "production"
})
```

---

## Database-Specific Tools
| Tool | Purpose | Required |
|------|---------|----------|
| CLI | Primary execution | Yes |
| API client | External service calls | Conditional |
| Validator | Output checking | Recommended |


### PostgreSQL
| Tool | Description |
|------|-------------|
| list_indexes | List all indexes |
| get_table_size | Get table size |
| vacuum_analyze | Optimize table |
| backup | Create backup |

### MySQL
| Tool | Description |
|------|-------------|
| show_processlist | Show running queries |
| kill_query | Kill long-running query |
| analyze_table | Analyze table |
| optimize_table | Optimize table |

---

## Use Cases
This section covers use cases for the database-mcp skill.
Key operations include input validation, core processing, and output verification.
Refer to the skill overview for detailed usage instructions.


### 1. Data Analysis
```
- Query customer data
- Generate reports
- Calculate metrics
- Export results
```

### 2. Schema Management
```
- Explore existing schemas
- Create new tables
- Modify columns
- Add indexes
```

### 3. Debugging
```
- Find slow queries
- Check connections
- Analyze locks
- Monitor performance
```

### 4. Migrations
```
- Generate migration scripts
- Apply schema changes
- Rollback if needed
```

---

## Integration with 1ai-skills
- Connects with existing toolchain via standard interfaces
- Supports webhook-based event notifications
- Compatible with CI/CD pipelines for automated workflows
- Provides structured output for downstream consumption


### With Development
```
code-reviewer → database-mcp → query-analysis
    ↓              ↓
Review code    Optimize schemas
```

### With Analytics
```
database-mcp → analytics-dashboard → reporting
    ↓              ↓
Extract data   Visualize
```

---

## Security Best Practices
This section covers security best practices for the database-mcp skill.
Key operations include input validation, core processing, and output verification.
Refer to the skill overview for detailed usage instructions.


### Do's
✅ Use read-only connections when possible  
✅ Parameterize queries  
✅ Limit table access with separate users  
✅ Enable query logging  
✅ Regular backups  

### Don'ts
❌ Don't expose admin credentials  
❌ Don't run without limits  
❌ Don't skip connection pooling  

---

## Version History

- **v1.0** (2026-02-27) - Initial creation
  - PostgreSQL, MySQL, SQLite support
  - 12+ MCP tools

---

## Related Skills

- [code-reviewer](../../development/code-reviewer/SKILL.md) - Code review
- [analytics-dashboard](../../marketing/analytics-dashboard/SKILL.md) - Data visualization
- [automation](../automation/) - Workflow automation

## How to Use

1. Invoke the skill when relevant domain keywords appear in the request
2. Provide required inputs as specified in the skill definition
3. Review the output for correctness before delivering to the user
4. Combine with related skills for complex multi-step workflows

## Verification

After completing this skill, confirm:

- [ ] Output meets the defined quality and completeness requirements
- [ ] All prerequisites are verified and documented
- [ ] Error handling covers edge cases
- [ ] Results are accurate and actionable

## Process

1. Analyze the task requirements
2. Apply domain expertise
3. Verify output quality