"Browser Automation Tools" matching MCP servers:

An advanced Playwright MCP server that enables efficient browser automation through compressed accessibility snapshots, sandboxed code execution, and visual element labeling. It features 90% DOM compression and integrated DevTools for deep web inspection and interaction.

An MCP server that provides a persistent sandbox for AI coding agents to explore codebases server-side, returning only compact summaries to reduce context consumption.

Provides a set of read-only Kubernetes functions via an MCP server, enabling interaction with Kubernetes clusters through agents or coding assistants like GitHub Copilot.

An intelligent MCP server that orchestrates multiple MCP servers with AI-enhanced workflow automation and production-ready context engine capabilities for codebase analysis.

MCP server wrapping DeepSeek's agent harness tools into minimal/standard modes, enabling persistent shell, file editing, search, job management, and more via natural language.

Guides problem-solving by breaking down complex problems into steps and recommending appropriate MCP tools for each stage, with confidence scores and rationales for tool suggestions.

Enables dynamic creation and execution of custom tools/functions in multiple programming languages at runtime, exposing them to MCP clients like Claude.

Enables secure Windows development automation by providing MCP tools for filesystem access, project builds, restricted PowerShell commands, and approved network fetches.

A Model Context Protocol server that provides PureScript development tools for AI assistants, enabling code analysis, type lookups, and IDE server management without requiring heavy IDE setup.

A comprehensive MCP server providing tools for AI agents to interact with code, including reading symbols, importing modules, replacing text, and sending OS notifications.

Enables AI assistants to perform controlled Linux system administration tasks like reading logs, managing services, cron jobs, WordPress, and executing sandboxed Python code, with strict security constraints.

Provides a headless session runtime for reactive compute graphs, enabling MCP-driven cell operations without a DOM or browser.

A meta-MCP server that orchestrates tools from multiple MCP servers, enabling complex Python workflows with loops and conditionals.

A Model Context Protocol server that provides Claude with a dedicated space for structured thinking during complex problem-solving tasks, helping improve its reasoning capabilities.

MCP server for full AutoCAD automation, AutoCAD LT automation, and headless DXF generation. It provides 8 consolidated tools for drawing, entity, layer, block, annotation, P&ID, view, and system operations via MCP stdio transport.

Enables automation of Google Jules AI coding assistant through task creation, code review automation, repository management, and AI-powered development workflows. Supports multiple session modes including cloud deployment with persistent authentication.

A Model Context Protocol server for time manipulation tasks, enabling AI models to get the current date/time and calculate duration between timestamps.

Enables AI agents to code and debug Commodore PET software using the VICE emulator, with CLI and MCP tools for session control, screen reading, memory manipulation, and testing.

Enables any MCP client to read, search, patch, and execute commands in a codebase, including interactive sessions and git operations, with permission modes and safety boundaries.

Enables users to create, manage, and execute Google Apps Script projects through natural language. It provides comprehensive tools for code editing, function execution, deployment management, and monitoring script processes.

Enables AI assistants to leverage Qwen's code analysis capabilities with large context windows, supporting file/directory analysis, sandbox execution, and multiple approval modes for safe code operations.

Connects AI assistants to live Roblox executor clients, letting the model run Luau in-game, walk the instance tree, decompile scripts, capture remote calls, and orchestrate work across multiple clients through 289 tools, a browser dashboard, and an in-game scripting surface. It also supports persistent playbooks, session traces, and verified agent workflows for repeatable automation.

A comprehensive Model Context Protocol server providing access to 70+ IT tools for developers and system administrators, including encoding/decoding, text manipulation, hashing, and network utilities.

A dynamic MCP server that automatically discovers Python files in a directory and exposes them as tools to any MCP-compatible AI client, allowing users to easily create and deploy custom AI tools.

A Model Context Protocol server providing AI assistants with comprehensive project, task, and subtask management capabilities with project-specific storage.

This MCP server gives an AI coding host controlled, client-agnostic access to a local machine's developer capabilities: transactional file edits, shell and PTY execution, Git and project inspection, language-server operations, isolated browser automation, Windows UI automation, VS Code state, durable jobs, and checkpoints, all bounded by filesystem root allowlisting and resource admission controls. It speaks standard MCP over stdio, Streamable HTTP, and legacy HTTP+SSE, and can also run headless as a long-lived job runner without any hosted model vendor.

Enables on-demand generation of TypeScript tools using an LLM with human-in-the-loop approval and safe sandboxed execution. It allows users to create and persist custom functionality through natural language requests.

Enables agents to control Google Colab notebooks through a secure, headless WebSocket architecture, allowing cell creation, editing, execution, and inspection without browser automation.

Enables agents to synthesize typed MCP tool schemas at runtime, validate Python ASTs for unsafe imports, compile sandboxed callable handlers, and hot-plug them into an active MCP runtime. It provides a zero-dependency, standard-library-only MCP server for safe just-in-time tool creation and execution.

Enables AI assistants to interact with multiple AI models through the OpenCode CLI with a unified interface. Supports plan mode for structured analysis, flexible model selection, and natural language queries with file references.