About the Project

The Challenge

Built a custom Model Context Protocol (MCP) server that connects Claude directly to a Supabase database — enabling Claude to query, insert, and manage database records through natural language during a conversation, without writing SQL manually.

The Approach

MCP is Anthropic's open protocol that standardises how AI models interact with external tools and data sources. My approach was to implement a Python-based MCP server that exposed Supabase database operations as callable tools — table queries, row inserts, filtered lookups, and record updates — all accessible to Claude through a defined tool schema.

I used the MCP Python SDK to define each tool's input schema, handle incoming tool call requests from Claude, execute the corresponding Supabase operation using the Python client, and return structured JSON results back to the model. This allowed Claude to reason about the data it retrieved and chain multiple database operations in a single conversation turn.

Cursor was used as the development environment for its native MCP client, which let me test Claude's tool calls interactively against the live server during development — seeing exactly what Claude requested and what the server returned at each step.

The Outcome

The practical result was Claude acting as an intelligent database interface — capable of answering questions like \"show me all users who signed up this week\" by autonomously constructing and executing the right Supabase query.