GibsonAI's MCP server (documentation-only repo; the runnable server ships with the `gibson-cli` package).
https://github.com/GibsonAI/mcpYour IDE just became your database management console. The GibsonAI MCP server brings full database lifecycle management directly into Cursor, Windsurf, Claude Desktop, and VS Code through natural language conversations.
You know the drill: designing schemas in one tool, writing migrations in another, testing queries in a third, then deploying through yet another interface. GibsonAI's MCP server eliminates this workflow fragmentation by putting database management where you're already working—right in your IDE's AI chat.
Instead of this workflow:
IDE → Database GUI → Migration tool → Query tool → Deployment dashboard → Back to IDE
You get this:
IDE chat: "Create a blogging platform with users, posts, and comments"
IDE chat: "Add a foreign key from bookings to payments"
IDE chat: "Generate test data for the booking table"
IDE chat: "Deploy this to staging"
The server handles the complex orchestration while you focus on building features.
Building a new feature:
"I need to add user authentication to this project. Create a users table with email, password hash, and session tracking."
Debugging production:
"Show me the schema for the payments table and run a query to find failed transactions from the last 24 hours."
Setting up development:
"Clone the production schema to a new dev environment and populate it with 100 fake users and their orders."
The server ships through their CLI package, so setup is just adding a JSON config block to your IDE:
{
"mcpServers": {
"gibson": {
"command": "uvx",
"args": ["--from", "gibson-cli@latest", "gibson", "mcp", "run"]
}
}
}
Works immediately in Cursor, Windsurf, Claude Desktop, VS Code with Copilot, and Cline. No additional dependencies or complex configuration.
Database management traditionally requires jumping between multiple specialized tools, each with their own interface and workflow. This creates friction that slows down development and increases the chance of errors.
By bringing database operations into your existing AI-powered development environment, you can iterate faster, make fewer mistakes, and keep your mental context intact. Your database becomes as easy to work with as asking your AI assistant to refactor a function.
The server connects to GibsonAI's database platform, which means you get production-grade database hosting with the convenience of chat-driven management. It's database administration that actually fits into modern development workflows.