Rapidapp MCP Server

The Rapidapp MCP Server bridges the gap between AI assistants and PostgreSQL databases hosted on Rapidapp. By exposing a Model Context Protocol interface, it lets developers ask an AI to create, query, and manage databases without writing any SQL or API calls. This is especially valuable in rapid prototyping scenarios where a developer wants to spin up a new database, generate boilerplate code, or retrieve metadata all through natural language.

The server implements standard MCP resources and tools that map directly to Rapidapp’s REST API. When an AI assistant receives a command such as “Create a new Rapidapp PostgreSQL database called ,” the MCP server translates that intent into an authenticated API request, returns the database ID and connection details, and feeds them back to the assistant. Developers can then use subsequent prompts like “Generate a Spring Boot CRUD service that connects to ” and the server will supply the necessary connection strings, enabling seamless end‑to‑end workflows.

Key capabilities include:

• Database lifecycle management: create, list, and inspect PostgreSQL databases.
• Application scaffolding: generate starter code for common frameworks (e.g., Spring Boot) that is pre‑wired to the created database.
• Secure authentication: all operations require a Rapidapp API key, ensuring that only authorized users can manipulate resources.
• Cross‑platform integration: the server is natively supported by popular MCP clients such as Claude Desktop, Cursor, Continue.dev, and can be installed via Smithery for a plug‑and‑play experience.

Typical use cases involve rapid MVP development, educational projects, or internal tooling. A product manager can ask an AI to “Set up a new database for the inventory system” and instantly receive a fully configured backend ready for integration. In continuous delivery pipelines, an AI could automatically provision test databases and tear them down after each run, reducing manual overhead.

Because the Rapidapp MCP Server speaks the same language as other MCP tools, it fits naturally into any AI‑augmented development workflow. Developers can chain commands—create a database, generate code, run migrations—all through conversational prompts, while the server handles authentication, error handling, and API orchestration. This reduces friction, speeds iteration, and allows teams to focus on business logic rather than infrastructure plumbing.