Local Scanner MCP Server

The Local Scanner MCP Server bridges the gap between an AI assistant and a developer’s local environment by providing direct, programmatic access to code files and localhost web applications. In practice, it lets an assistant like Claude or Cline interrogate a running server on , capture logs, take screenshots, and run linting or HTML validation—all without leaving the AI’s interface. This tight coupling removes the friction of context switching between an IDE, a browser, and command‑line tools, making it easier for developers to iterate on UI changes or debug runtime issues with AI guidance.

At its core, the server exposes four purpose‑built tools. visits a local URL, records console output, and can simulate user interactions such as clicks or text entry before reporting any runtime errors. captures a visual snapshot of the page, optionally scrolling to render the entire document. runs a language‑specific linter on JavaScript, TypeScript, or CSS files to surface style violations and potential bugs. checks either raw HTML or a local URL against web standards, flagging accessibility or markup issues. Each tool is intentionally simple to invoke but powerful enough for common local‑dev workflows.

Developers benefit from the server’s ability to embed these checks into AI prompts. For example, an assistant can automatically lint a newly edited component after it’s saved, or run to confirm that a login flow no longer throws console errors. The screenshot tool is ideal for generating visual regression tests or feeding UI snapshots into a design‑review workflow. By validating HTML on the fly, teams can catch accessibility violations before they reach staging or production.

Integration with MCP clients is straightforward: the server registers its capabilities via the standard MCP descriptor, and any compliant client (VSCode’s Cline, WindSurf’s Cascade, or custom tooling) can discover and invoke the tools with a single JSON payload. The server’s lightweight design means it can run locally on any machine, keeping sensitive code and data out of external services while still providing the same level of automation that cloud‑based AI tools offer.

In short, the Local Scanner MCP Server empowers developers to harness AI assistance directly within their local development stack. By offering on‑demand code linting, runtime diagnostics, and visual validation, it turns an otherwise isolated IDE into a collaborative, AI‑augmented workspace that speeds up debugging, enforces quality standards, and streamlines the feedback loop between code changes and UI behavior.