"Tools and Resources for Browser Automation" matching MCP servers:

MCP server for AI browser automation with tools for navigation, actions, data extraction, and scripting, supporting local and cloud execution.

Enables MCP clients to run complete browser workflows through a single run_workflow tool, with anti-detection backends, intelligent element location, automatic retries, and session persistence.

Windows desktop automation MCP server enabling screenshot capture, precise visual locating of UI elements via vision models, and automated mouse clicking.

Enables governed browser automation for AI agents with human-in-the-loop approval, audit logging, and read-only replay, supporting both ASK and AUTO autonomy modes.

Enables browser automation through MCP with native Playwright operations, deterministic assertions, and natural-language grounded actions, structured extraction, and bounded agent workflows over live page elements.

Enables the automatic generation of complete Live2D models from a single photo by automating segmentation, rigging, and physics configuration. It provides a full pipeline for creating layered art meshes and motion files through a suite of specialized animation tools.

Enables AI agents to control a real, persistent Chrome browser over MCP, perceiving pages as accessibility trees and interacting with elements by their accessible names without automation fingerprints or site-specific glue.

Enables MCP clients to manage SQLite-backed TODOs and schedule durable coding-agent jobs over stdio, with persistent job memory, run history, and a read-only dashboard.

Enables ChatGPT to inspect Jobber data and manage controlled automations with scheduling, approval workflows, and audit trails.

A local MCP server that enables AI applications like Claude Desktop to securely access and work with Obsidian vaults, providing capabilities for reading notes, executing templates, and performing semantic searches.

Enables AI agents to drive desktop CAD software through natural language with verified execution, failure recovery, and traceable results across modeling, assemblies, drawings, exports, motion, FEA, and related engineering workflows.

Browser use using Typesafe's Jev model

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Self-hosted MCP server for AI browser automation. Connects to your own Chromium instance via CDP, providing tools for browser control, navigation, interaction, and content extraction.

Gives an AI assistant a persistent, stealth-configured Chrome browser that stays logged in across sessions, supports interactive first login, and can autofill credentials from the macOS Keychain and replay WebAuthn passkeys for sites that block scripted login.

Enables AI assistants to control a web browser through Playwright-compatible tools, with an on-device decision engine for autonomous task completion and optional LLM escalation.

Enables AI agents to navigate the web visually using screenshot-based interaction and Set-of-Mark labeling for interactive elements. It supports humanized browsing behaviors, anti-detection measures, and complex tasks like multi-click CAPTCHA solving.

An MCP server that enables AI agents to control a real Chrome browser with full login state through 37 structured automation tools, connecting via the Playwriter extension without needing a remote debugging port.

Provides computational tools for systematic reasoning, including boolean evaluation, date arithmetic, object counting, state tracking, and format validation, to enhance agent capabilities and eliminate calculation errors in reasoning tasks.

Enables AI agents to control your installed Google Chrome through MCP or HTTP using compact text snapshots, exact pixel coordinates, and a visible cursor. It provides browser tools for navigation, clicking, typing, scrolling, tabs, forms, waiting, recording, and human handoff.

Gives AI agents a single shared, logged-in Chrome they can drive over MCP or plain HTTP: open and read tabs, click, type, upload files, run short Playwright scripts, hand off whole web tasks to a cheaper model, and keep per-site memory. Agents work in background windows they own without stealing the user's mouse or closing their tabs.

Enables AI agents to control a persistent Chrome browser through a local daemon, with Jev performing routine actions and the host agent handling reasoning, text, and verification.

Enables browser automation in which a planning LLM states one outcome at a time while a Typesafe System One model decides which element, action, and value to use, with Playwright carrying it out. Exposes tools for opening pages, driving multi-step goals, checking or choosing among options, reading relevant page text, acting on elements directly, and calling a page's own WebMCP tools.

An MCP server that lets Claude control a Minecraft bot with 40+ actions including movement, combat, crafting, and inventory management. Built on Mineflayer, it supports Microsoft authentication, pathfinding, and auto-reconnect.

Enables browser automation where a calling LLM states one desired outcome per step and a separate decision model chooses the element, action, value, and completion status, with Playwright carrying out the action. Exposes tools for navigating, performing and verifying steps, reading question-relevant page text, taking snapshots, capturing screenshots, and invoking tools that pages register for agents.

Enables browser automation through MCP clients like Claude or Cursor, using the client's existing LLM without requiring an additional API key.

Enables MCP clients to automate a real browser by stating one outcome at a time in natural language, with a decision model (Jev) choosing each element, action, and value while code drives Playwright. Also exposes tools to open pages, verify questions, read page content, snapshot elements, act directly, and call a page's WebMCP tools.

Enables an LLM to drive a real browser by declaring one outcome at a time, while Jev chooses the element, action, and value and Playwright executes it, returning a clear status such as done, blocked, or needs confirmation. Also exposes tools to open pages, ask yes/no or multiple-choice questions about a page, read question-relevant page text, capture snapshots and screenshots, act on elements directly, and invoke a page's own WebMCP tools.

It lets LLM clients drive a browser by specifying outcomes while a TypeSafe System One model chooses each action and Playwright executes it. It also provides tools for checking page state, selecting among options, snapshots, and direct actions.

Enables AI agents to drive the Chrome, Brave, or Edge browser you are already logged into, working in a tab of its own with a visible cursor and real trusted input. You can pause, take over, or hand back control at any time, and consequential actions such as submitting, paying, sending, deleting, or uploading wait for your approval.