"Information or resources about playwrights or the Playwright framework" matching MCP servers:

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution

A TypeScript framework for building Model Context Protocol (MCP) servers with automatic discovery and loading of tools, resources, and prompts.

A Model Context Protocol server that enables Claude to execute Python code using boto3 to query and manage AWS resources directly from conversations.

Enables AI agents to directly manipulate Jupyter Notebook cells and structure through a secure, well-defined API, overcoming Cursor's AI agent mode limitations.

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.

Enables a bot to inspect, query, create, edit, and script Roblox Studio instances in token-cheap batches, plus run Luau, playtests, screenshots, and inputs through Roblox's official Studio MCP connection. It runs locally over stdio or an authenticated local HTTP endpoint, returning small structured answers instead of dumping whole games into context.

A general-purpose MCP server that provides utility tools for echo, date/time, and file operations within Claude Code and Claude Desktop. It functions as an extensible framework designed to help developers easily build and register custom Python-based tools.

A comprehensive framework for building reliable Python MCP servers that enforces incremental development practices through Cursor Rules, featuring built-in security measures and a smart rule system.

Gitbub mcp

An MCP server that lets AI models run code in 31 languages, evaluate symbolic math and logic problems, and measure complexity—exposed as 48 tools for execution, session management, translation, optimization, and more.

Ephemeral MicroVM-isolated code execution for AI agents. Run Python, Node, or bash — fresh hardware-isolated VM per call, hard-purged after. No state persists between calls.

MCP server that gives AI assistants a secure gVisor-isolated sandbox to run Python or JavaScript code, returning stdout, stderr, and exit codes without local access.

Sandboxed Python execution with automatic dependency management. Executes Python scripts in isolated environments (bubblewrap or Docker) with PEP 723 inline dependencies, preventing host pollution.

Run real Playwright E2E tests from your AI coding agent.

Enables any MCP client to evaluate Wolfram Language code in a persistent local Mathematica or Wolfram Engine kernel, export results to common file formats, and inspect or manage kernel status without cloud APIs, API keys, or runtime dependencies.

Cloud GPU rendering for Blender, built for AI agents. Preview .blend files or bpy scripts, estimate render time, and render images, animation frames, or MP4 videos without a local GPU. Connect via MCP (OAuth) with Claude, ChatGPT, Codex, or Cursor: https://render.janction.jp/mcp. Get ¥100 in credits without a card, plus ¥400 after card registration. Then ¥0.1 per GPU-second.

A FastMCP server that turns JSON data into Plotly figures, deployable as an isolated service on Modal. Data goes in as JSON; a validated Plotly figure (JSON) or a rendered PNG comes back over the Model Context Protocol.

Lets an agent load a design once into a long-lived OpenSTA session and then run static timing and power analysis through dedicated tools or arbitrary Tcl commands. Enables setup/hold slack, TNS/WNS, fmax, DRV, and power queries against the live session.

Enables coding agents to run multiple approaches or tasks in parallel on isolated Daytona sandboxes, returning tested diffs and benchmark rankings so the best outcome can be applied.