MCP File Preview Server

The MCP File Preview Server tackles a common bottleneck for developers who need to evaluate and analyze local HTML files within an AI‑assisted workflow. Traditional debugging of web pages often requires opening a browser, inspecting elements, and manually capturing screenshots or parsing the DOM. This server automates those steps by exposing two straightforward tools—preview_file and analyze_content—that can be invoked directly from Claude or any MCP‑enabled client. By rendering the page in a headless browser, it guarantees that CSS and JavaScript are fully applied, producing an accurate visual snapshot without manual intervention.

At its core, the server captures full‑page screenshots of any local HTML file and stores them in a dedicated directory. The screenshot tool accepts optional width and height parameters, allowing developers to tailor the viewport to specific device dimensions. The accompanying analyze_content tool parses the rendered DOM and returns a concise summary of structural elements such as headings, paragraphs, images, and links. This quick statistical overview helps teams spot missing content or broken navigation before the page goes live, streamlining quality assurance processes.

Key capabilities include:

• Local file handling – The server accepts absolute or relative paths, automatically resolving local resources like images and stylesheets.
• CSS‑aware rendering – By leveraging a headless browser engine, the screenshots reflect exactly what users would see, including responsive layouts and dynamic content.
• Structured analysis – The tool returns counts of common HTML elements, making it easy to programmatically validate page structure or generate reports.
• Integration with MCP workflows – Both tools are exposed via the standard MCP SDK, so they appear in the tool selector of any compatible AI assistant and can be chained with other tools or prompts.

Real‑world scenarios that benefit from this server include:

• Content auditing – Quickly verify that all required headings and images are present on a landing page before publishing.
• Visual regression testing – Capture screenshots of prototype pages and compare them against baseline images as part of an automated CI pipeline.
• Documentation generation – Embed live previews of HTML snippets directly into technical docs or knowledge bases, ensuring that examples stay up to date with the source files.
• Rapid prototyping – Allow designers and developers to iterate on layout changes, instantly previewing the result without leaving their IDE or AI chat.

Because the server is built on the MCP SDK, it inherits robust tooling for debugging and inspection. Developers can launch the MCP Inspector to confirm tool availability, inspect request payloads, and troubleshoot issues directly from the command line. This tight integration with existing MCP tooling means that adding file preview and analysis to an AI workflow requires minimal configuration—just a single entry in the MCP settings of Claude or VS Code.

In summary, the MCP File Preview Server transforms static local HTML files into interactive assets for AI assistants. By providing accurate screenshots and structural insights through simple, declarative tools, it empowers developers to validate design intent, catch content gaps, and automate quality checks—all within the conversational context of their favorite AI platform.