Selenium MCP Server

Selenium MCP Server – A Web‑Automation Bridge for AI Assistants

The Selenium MCP Server transforms a standard Selenium WebDriver instance into an MCP‑compatible service that AI assistants can query as if they were calling a native tool. By exposing a rich set of web‑interaction capabilities—navigation, element manipulation, screenshot capture, JavaScript execution, and more—the server eliminates the need for developers to write custom connectors or embed browser automation logic into their assistants. Instead, a single HTTP endpoint provides a declarative API that any MCP‑compliant client can consume.

At its core, the server offers a toolset that mirrors common browser actions. Developers can instruct an assistant to open a URL, locate elements by text, class, ID, attributes, or XPath, and perform clicks or input typing. For advanced workflows, the server supports pagination of element queries, child‑node filtering, and iFrame targeting. Once an element is identified, the assistant can retrieve its CSS styles or computed properties, enabling dynamic UI analysis. Capturing full‑page screenshots is also straightforward, allowing visual verification or debugging of rendered pages.

Beyond interaction, the server enriches automation with JavaScript execution and logging. Clients can inject arbitrary scripts into the page context, optionally capturing console output for debugging or result extraction. Browser logs—both console and network traffic—are exposed with level and URL filtering, giving assistants insight into runtime errors or API calls without manual inspection. Local storage operations are fully supported; an assistant can add, read, update, or delete key/value pairs, facilitating stateful interactions across multiple requests.

Typical use cases include automated web testing, where an AI can generate test scenarios, navigate through a site, assert element states, and report failures. In data extraction, the assistant can scrape structured information from dynamic pages, capture screenshots for audit trails, and store results in local storage or external databases. For content moderation or SEO analysis, the server allows AI to load pages, evaluate rendering quality, and capture performance metrics—all through simple tool calls.

Integration into AI workflows is seamless. An MCP client—such as a Claude or OpenAI model configured with the Protocol—simply declares a tool usage (e.g., ). The server interprets the call, performs the action via Selenium, and returns a structured JSON response. Because the protocol handles tool discovery and schema validation automatically, developers can add new tools or modify existing ones without changing the client code. This plug‑and‑play nature makes the Selenium MCP Server a standout component for building scalable, maintainable AI‑driven web automation pipelines.