"Information about Puppeteer (Node.js library or related topics)" matching MCP servers:

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

Enables coding agents to establish exact-release library identity, search provenance-tracked API, docs, example, source, and release evidence, compare releases, and test proposed invocations in isolated capsules for Rust and Python dependency environments.

Enables AI agents to interact with Android devices through visual UI element detection and automated interactions. Provides comprehensive Android automation capabilities including touch gestures, text input, screenshots, and video recording via uiautomator2.

An advanced MCP server for browser automation using Puppeteer, specifically optimized for token efficiency through minimal data returns and progressive enhancement. It enables agents to navigate pages, capture LLM-optimized screenshots, extract structured content, and perform batch interactions.

Enables users to manage, search, render, version, and regression-test local Markdown templates with typed variables, and to expose them as MCP tools and native prompts without requiring a model API, account, or cloud service.

Enables AI-assisted development by providing a library of 110+ curated prompts, workflows, and coding standards, with MCP tools for prompt retrieval, composition, and multi-step workflow chains.

Enables automatically generating standalone MCP servers from any Python library, exposing its functions as deterministic callable tools.

Serves Markdown skill and rule files from a local directory to AI agents on demand, letting them list and fetch specific instructions without context bloat.

An MCP server that scans React and Vue projects, extracts component metadata (props, slots, events, imports, usage), and exposes it to AI coding agents via structured tools.

Provides AI assistants with access to design documentation across multiple code libraries, enabling discovery of existing utilities and patterns to avoid reimplementation.

An MCP server that enables users to manage, search, and apply specialized AI personas within Claude Desktop and Claude Code CLI. It features a local-first architecture with YAML-based storage for organizing curated prompts and role collections.

Enables AI assistants to debug Node.js applications using Chrome DevTools Protocol. Provides comprehensive debugging capabilities including breakpoints, stepping, variable inspection, expression evaluation, and console monitoring.

A comprehensive prompt library for frontend developers covering React, frontend best practices, and coding guidelines, accessible via MCP tools.

Search and retrieve Google Apps Script libraries with AI-generated summaries and usage examples directly from MCP clients.

Provides AI assistants with access to private React component library documentation, props, and code examples through type-safe TypeScript integration.

An MCP server that enables searching for specific files by name within the current directory and its subdirectories. It uses Server-Sent Events (SSE) to provide a find_file tool for locating local files and libraries.

Provides a small educational library MCP server that demonstrates core Model Context Protocol concepts through book search, checkout, resource reading, prompts, and tool annotations, enabling developers to explore MCP mechanics interactively.

Provides comprehensive system diagnostics and hardware analysis through 10 specialized tools for troubleshooting and environment monitoring. Offers targeted information gathering for CPU, memory, network, storage, processes, and security analysis across Windows, macOS, and Linux platforms.

Provides Node.js debugging capabilities with process management for AI agents, allowing them to start/stop Node.js processes, set breakpoints, step through code, and evaluate expressions.

Enables querying Node.js API documentation, including searching for modules and listing all available modules with their methods.

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.

A basic MCP server that provides arithmetic calculation tools and system information retrieval capabilities, including platform, CPU, and memory details.

Exposes a Node.js REST API for user and product management through MCP tools, allowing AI assistants to directly interact with MongoDB to create, read, update, and delete users and products.

Serves as a practical starting point for AI agents, providing a stateless HTTP-based MCP endpoint with validated example tools for time queries, text formatting, and arithmetic calculations.

MCP server for verified reuse infrastructure that lets agents query before work to obtain safe, permissioned results (exact component, source-free method, or abstention) with receiver-owned verification and non-disclosure guarantees.

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

Proxies MCP tools from Mingdao cloud, enabling Coze to use them securely without exposing Mingdao tokens.

Enables programmatic access to EndNote .enl libraries, allowing users to list, search, and extract full text from bibliographic references and their attached PDFs through MCP tools.

Enables AI agents to search and browse a curated catalog of 330+ third-party APIs and MCP servers using tools like search_apis, get_api, get_reviews, and list_categories, with no API key required.

Provides coding agents with 63+ bounded, verifiable work loops, enabling goal-driven loop selection and executable protocol generation via MCP tools.