| name | pgadmin-mcp-connector |
| description | MCP connector for pgAdmin PostgreSQL administration – enables AI-powered database management, query building, and server monitoring through Claude |
| license | PostgreSQL License |
| tags | ["data","postgresql","mcp","pgadmin","database"] |
| difficulty | intermediate |
| time_to_master | 4-8 weeks |
| version | 1.0.0 |
Pgadmin MCP Connector
Overview
This skill enables Claude to interact with Pgadmin through the Model Context Protocol (MCP). It provides a bridge between Claude's AI capabilities and Pgadmin's REST API, allowing natural language control of Pgadmin operations, intelligent automation, and AI-powered assistance for Pgadmin workflows.
When to Use This Skill
- PostgreSQL query generation and optimization
- Server and database configuration management
- Backup and restore operation management
- User role and permission administration
- Performance dashboard analysis
Architecture
┌─────────────┐ ┌─────────────────┐ ┌──────────────────┐
│ Claude │────▶│ MCP Server │────▶│ Pgadmin │
│ (Client) │◀────│ (TypeScript) │◀────│ (REST API )│
└─────────────┘ └─────────────────┘ └──────────────────┘
Core Concepts
MCP Server Setup
The connector implements an MCP server that exposes Pgadmin operations as tools Claude can invoke. The server translates natural language intentions into REST API calls.
Key Endpoints/Interfaces
/api/browser/server, /api/sql, /api/dashboard, /api/backup, /api/restore
Implementation
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";
const server = new McpServer({
name: "pgadmin-mcp-connector",
version: "1.0.0",
});
server.tool(
"list_resources",
"List and query Pgadmin resources with optional filters",
{
query: z.string().optional().describe("Search query or filter"),
limit: z.number().optional().describe("Max results to return"),
},
async ({ query, limit }) => {
const response = await fetch(`${BASE_URL}/api/browser/server`, {
headers: { "Authorization": `Bearer ${API_KEY}` },
});
const data = await response.json();
return {
: [{ : , : .(data, , ) }],
};
}
);
server.(
,
,
{
: z.().(),
: z.({}).().().(),
},
({ name, config }) => {
response = (, {
: ,
: {
: ,
: ,
},
: .({ name, ...config }),
});
data = response.();
{
: [{ : , : }],
};
}
);
server.(
,
,
{
: z.().(),
: z.().().(),
},
({ , timeframe }) => {
response = (, {
: { : },
});
data = response.();
{
: [{ : , : .(data, , ) }],
};
}
);
transport = ();
server.(transport);
Claude Desktop Configuration
{
"mcpServers": {
"pgadmin-mcp-connector": {
"command": "node",
"args": ["path/to/pgadmin-mcp-connector/index.js"],
"env": {
"PGADMIN_API_KEY": "your-api-key",
"PGADMIN_BASE_URL": "https://your-instance-url"
}
}
}
}
Best Practices
- Authentication: Store API keys securely using environment variables; never hardcode credentials
- Rate Limiting: Implement request throttling to respect Pgadmin API rate limits
- Error Handling: Provide clear, actionable error messages for common failure scenarios
- Pagination: Handle paginated responses for large datasets efficiently
- Caching: Cache frequently accessed read-only data to reduce API calls
- Security: Validate all inputs before passing to the Pgadmin API; sanitize outputs
- Logging: Log all API interactions for debugging and audit purposes
Example Prompts
"Create a read-only user with access to the analytics schema and set up automated daily backups"
Security Considerations
- All API credentials must be stored as environment variables
- Implement input validation and sanitization for all tool parameters
- Use HTTPS for all API communications
- Follow the principle of least privilege for API token permissions
- Audit log all write operations for compliance tracking
Resources
Changelog
| Version | Date | Changes |
|---|
| 1.0.0 | 2026-04-01 | Initial MCP connector skill |
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