"Using Python to Locate and Retrieve Browser Element Selectors" matching MCP servers:

Enables AI agents to search, browse, and read a field-tested Xperience by Kentico knowledge pack, fetch checklists and blog articles, request consultations, and access L402-gated premium playbooks via Lightning payment.

Enables autonomous agents to anchor browser elements from vision inputs, providing stable DOM references resilient to click drift for reliable computer-use automation.

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

An MCP server enabling AI agents to drive a real browser through residential proxies with per-task geo (country/city) and sticky identity, all chosen at call time.

A local stdio MCP server that drives your Chrome browser through the Asklear extension, offering six browser tools for navigation, observation, clicking, filling, scrolling, and extraction — all operations remain on your machine.

Enables LLMs to query live data from over 250+ sources via CData Python Connectors using natural language. Wraps connectors as a Model Context Protocol server.

MCP server that drives a user's real Chrome browser via a WebSocket-connected MV3 extension, enabling tab management, navigation, page interaction, screenshots, and script evaluation through natural language.

Enables AI agents to inspect and modify Chrome state directly through extension APIs, listing tabs and windows and moving or reordering tabs within and across windows. Operations are validated and never simulate mouse/keyboard input, steal focus, or activate tabs implicitly.

Enables MCP-capable clients to launch and control one visible, isolated Chromium session, creating and managing Tether-owned tabs, navigating to HTTP(S) URLs, reading bounded page text on request, and ending the session without touching the user's personal browser profile.

MCP server that wraps sendblue-browser-use's HTTP API, providing tools to control a stealth-patched Chromium browser with persistent sessions, navigation, screenshots, and script execution.

MCP server that gives AI full control of a live Chrome browser via CDP, with 145 tools for framework-aware intelligence, evidence analysis, and SEO auditing. Connects to your existing Chrome via an extension, enabling interaction with dynamic and authenticated web pages.

Enables secure execution of Python code in a sandboxed WebAssembly environment using Pyodide and Deno. Automatically handles package management and captures complete execution results including stdout, stderr, and return values.

Exposes the SiftingIO market-data SDK to AI assistants, enabling live prices, fundamental data, and market information retrieval.

An open-source MCP server that provides browser automation capabilities to external AI systems, enabling navigation, DOM interaction, and web content extraction.

MCP server providing browser automation for AI agents, enabling actions like clicking and typing, structured data extraction, content validation, multi-step task execution, and memory enrichment from web pages.

Enables AI agents to securely control a user's existing Chrome profile locally, providing typed browser actions, form and editor support, WordPress workflows, terminal automation, and Figma inspection with policy-based authorization and redacted auditing.

Enables secure browser automation by letting agents fill Turnkey-stored secrets into web forms without the secret values ever appearing in the conversation, transcript, or model context.

Implementation of an MCP server for the RAG Web Browser Actor. This Actor serves as a web browser for large language models (LLMs) and RAG pipelines, similar to a web search in ChatGPT.

This MCP server lets AI agents connect to Figma to read, analyze, create, and modify designs, including elements, styles, assets, and code generation. It works with free Figma accounts and supports parallel multi-agent use across MCP-compatible clients.

A Machine Comprehension Protocol server that enables AI assistants to interact with Kestra workflows through natural language, supporting operations like flow management, executions, backfills, and other Kestra features.