"MCP servers for Selenium with TypeScript" matching MCP servers:

Provides browser automation using Selenium, supporting Chrome and Firefox, with tools for navigation, element interaction, screenshots, and more.

A production-ready MCP server that exposes Selenium 4 browser automation as MCP tools.

A tool that enables automated browser control using Pyppeteer within the MCP framework, allowing navigation, screenshot capture, and element interaction with websites.

Enables AI coding agents to diagnose and repair Python Selenium UI automation using real evidence from live DOM and test runs, with enforced safety boundaries and verifiable fixes.

Exposes Selenium WebDriver as an MCP server, enabling AI agents and LLMs to control real browsers for automation tasks like navigation, element interaction, and screenshot capture.

An MCP server for web automation using Selenium WebDriver, enabling AI assistants to navigate, interact with elements, take screenshots, and manage browser storage.

Enables browser automation by managing Selenium Grid browser instances (Chrome, Firefox, Edge) in Docker or Kubernetes environments. Provides secure, scalable browser control for AI agents and testing workflows.

A server implementation that enables controlling web browsers programmatically through Claude's desktop application, providing comprehensive Selenium WebDriver operations for browser automation with Chrome and Firefox support.

Enables LLMs to automate browser tasks (navigation, clicks, text input) via Selenium through the Model Context Protocol.

Enables AI harnesses to maintain a persistent memory layer backed by a local SQLite file, providing MCP tools to add, search, deprecate, and synchronize facts without deleting history.

A complete Model Context Protocol server that implements Selenium WebDriver for browser automation with advanced detection evasion capabilities, multi-browser support, and comprehensive web interaction functionalities.

A learning MCP server that demonstrates tools and resources using FastMCP, with a greet tool and UI capabilities.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

Provides seamless access to the Protein Data Bank in Europe (PDBe) API and search capabilities, enabling AI clients to query protein structures, perform advanced searches, and retrieve structural biology data.

A workspace of six MCP servers—grounded-cv (hybrid RAG with citations), repo-intel (GitHub repo intelligence), web-research (safe web search/extraction), ats-jobs (unified ATS job boards), outcome-ledger (durable task ledger), and coding-workflows (code review & planning)—purpose-built for agentic hiring evaluations.

Provides a framework for running multiple MCP servers using FastAPI, stdio, and streamable-http transports, with an echo tool for testing and integration with MCP Inspector.

Automatically fixes broken Selenium test locators when UI changes occur, reducing test maintenance overhead.

Provides 7 MCP servers with 95 tools for git, GitHub, .NET, Ollama, Rust, template sync, and Python, enabling natural-language commands to perform real development operations.

Provides tools for DeepTempo AI SOC including findings and case management, investigation workflow orchestration, action approval workflows, and MITRE ATT&CK layer generation.

Open-source MCP servers for ESG data extraction, analysis, and regulation management, providing 31 tools across 6 servers for tasks like metrics extraction, PDF processing, vector storage, and web scraping.