Debugg AI MCP Server

Overview

Debugg.AI’s MCP server brings a full‑featured, AI‑driven testing and debugging platform directly into the Model Context Protocol ecosystem. It solves a common pain point for developers: coupling test automation, live monitoring, and continuous integration into the same workflow that AI assistants use to reason about code. By exposing a rich set of tools over MCP, the server allows Claude or other AI agents to orchestrate end‑to‑end browser tests, capture real‑time diagnostics, and manage test suites—all without leaving the conversational interface.

At its core, the server implements a suite of twelve focused development tools. The most prominent are the E2E testing utilities that let an AI agent run browser tests defined in natural language, create organized test suites for features, and generate commit‑based tests automatically. Live session monitoring tools provide instant feedback on console output, network traffic, and visual changes through screenshots. Test management commands expose a convenient API for listing, creating, and tracking both standard and commit‑based test suites. Together, these capabilities give developers a single entry point to initiate, observe, and analyze tests from any MCP‑compatible client.

The value for developers lies in the zero‑configuration, end‑to‑end experience. Once authenticated with an API key, a developer can trigger complex test scenarios or start a live debugging session simply by instructing an AI assistant. The server’s integration with the Debugg.AI dashboard ensures that all results, logs, and screenshots are centrally stored and easily accessible. This seamless CI/CD integration means that AI‑generated tests can be run automatically on every push, providing instant quality feedback.

Real‑world use cases include automated regression testing after a code merge, exploratory testing during feature development, and rapid debugging of UI glitches. For example, an AI assistant can be asked to “test the ability to create an account and login,” which launches a browser session, executes the steps described in natural language, captures screenshots at each stage, and reports success or failure—all visible to the developer in real time. This tight coupling of AI reasoning with live observability accelerates defect detection and reduces manual test writing effort.

Unique advantages stem from the server’s universal compatibility with any MCP‑ready client and its comprehensive toolset that covers the entire testing lifecycle—from test creation to live monitoring. By exposing these capabilities through MCP, Debugg.AI empowers developers to embed sophisticated testing workflows directly into their AI‑augmented development pipelines, turning conversational prompts into actionable, observable test executions.