"Using the web version of Perplexity AI" matching MCP servers:

Bridges the editing capabilities of an already-open DingTalk document in the browser to any MCP host via standard stdio, forwarding tools to the page's internal MCP server over a local WebSocket. Supports read/write operations through suggested edits, pairing-based security, and zero runtime dependencies.

A TypeScript-based MCP server that enables AI assistants to execute HTTP requests with full control over methods, headers, and body content. It facilitates seamless interaction with web APIs and endpoints through a versatile tool that handles automatic JSON formatting and response truncation.

Runs 20 slash-command workflows across Google Calendar, Gmail, Linear, Slack, Granola, Google Docs, GitHub, Stripe, Notion, Google Forms, Sheets and Drive to produce morning briefs, meeting prep, action items assigned to owners and weekly updates. Reads proceed without asking, while anything that creates, sends, changes or deletes is shown for approval first.

Enables AI assistants to create and manage visual automation configurations, workflows, and UI states through the Qontinui API. It supports project management, workflow execution, and configuration handling for automated web interactions.

Whatsapp-Web MCP

MCP server that lets Claude read and send WhatsApp messages using a genuine WhatsApp Web client behind a code-enforced human-behavior middleware for safety.

Enables AI assistants to interact with humans through GUI dialogs for text input, choices, confirmations, and information display.

Enables AI assistants to present multiple UI component designs in a browser for visual selection, with AI-powered design generation using MiniMax-M2.1 from natural language prompts or manual HTML input.

Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.

An AI-powered MCP server that automates web testing workflows by enabling recording, execution, and discovery of tests through natural language prompts.

Connects ChatGPT Web to a local development environment, enabling file reads and patches, shell execution, plan updates, and isolated worktree coordination through permissioned MCP tools.

Acts as a bridge between an AI assistant and a WebApp Tinkerer instance, enabling live inspection and manipulation of applets in the browser.

An MCP server that enables AI assistants to programmatically create and manage flowcharts, ERDs, and swimlane diagrams. It provides tools for manipulating diagram structures, performing auto-layouts, and exporting to Mermaid or Markdown formats.

Enables natural-language control and generation of Office documents and contact lookups via MCP, with LangGraph-based planning, execution, quality checking, and repair, plus batch processing, a FastAPI/Web console, and Docker deployment.

Enables authenticated MCP clients to automate UI-only operations on Digital Invoicing Software via Playwright, including login/session checks, navigation, dashboards, invoice validation/edit/duplication/export, reporting, screenshots, and user management with per-tenant isolation.

Enables natural-language CAD geometry creation in Autodesk Fusion 360 by connecting an LLM running in WSL via OpenCode to Fusion on the Windows host.

Provides AI-powered educational tools for teachers including lesson planning, quiz creation, student progress analysis, learning path recommendations, and rubric generation. Enables educators to automate administrative tasks and personalize learning experiences through natural language interactions.

An MCP server for converting App Store Optimization (ASO) data from platforms like App Store Connect into Web SEO data. It enables the creation of synced websites, keyword research, and automated blog content generation based on app store metadata.

Remote-control Unity Editor from any AI IDE via file-based IPC — 62 tools, zero dependencies

Manage Job using MCP: Manage Job, Candidates, Resumes, Salaries all within this one MCP tools It can solve problems like: You have 50 resumes to screen. Your AI assistant can reason about candidates, but it can't: Read PDFs/DOCX — The AI can't open binary files Extract structured data — Copy-pasting loses formatting, metrics, and context Compare at scale — No consistent scoring across candida