"Using MCP to Control the Vivaldi Browser" matching MCP servers:

Enables Claude Code and Claude Desktop to control your own Chrome browser, with Jev deciding each click, keystroke, and scroll.

Enables structured learning with a verified loop: define goals as observable claims, learn through teach-lab-test-gate per claim, and get independently graded by an adversarial examiner to ensure genuine progress.

MCP server that gives Claude Code full mouse, keyboard, and app control on macOS. Tell Claude what to do and watch it operate your computer.

Browser use using Typesafe's Jev model

MCP server for The Commons (jointhecommons.space), a persistent, noncommercial space where AI voices from different models post and reply to each other with persistent identities. 48 tools; reading needs no token, writing uses a facilitator-issued token.

Enables safe automation of Chrome browser through a local MCP server and Chrome extension, allowing LLMs to control browser tabs, pages, and computer-use actions with permission controls.

AI-native orchestration layer with 80+ tools for task management, code editing, browser automation, terminal control, and persistent memory across CLI, local MCP, and cloud deployments.

A governance and control layer for MCP tools that manages tool requests as intents through policy-based approval, queuing, or blocking. It enables secure human oversight and audit trails for consequential agent actions across platforms like Claude Desktop and Cursor.

Enables an agent to run a single planning request past seats drawn from multiple AI labs, which ask clarifying questions, propose independently, debate each other's anonymised proposals, and panel-review a draft against yes/no acceptance criteria until it passes or hits the round cap. Each run writes a local folder with the deliverable, the full debate board, a handoff document, per-lab scores, and real token/cost accounting, all driven with your own API keys.

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 users to deploy a production-grade control plane for agents, providing a spec-compliant MCP server, scoped tool grants, failure-mode detection, and cost governance.

Connects AI agents to The Agents Hub, visualizing them as pixel characters on a tile-based property with tools for state, assets, inboxes, and multi-agent orchestration.

Serves a loopback-only MCP endpoint that lets a same-machine client start, steer, and cancel DSH Sessions it knows by id, list their durable subagent trees, deliver messages to continuable children, and read durable event logs with paging and chunked oversized-event recovery. It maps every call onto native Session Controller and subagent services without owning task state, starting a second listener, or registering model-facing tools.

Enables coding agents to request, track, and verify independent cross-model reviews with structured findings, attachment hashes, and provenance receipts via Chrome Bridge, Codex, or Responses transports.

Enables one coding agent to inspect, configure, debug, and repair another agent over stdio MCP, with redacted reads and confirm-gated writes and restarts.

Enables reviewing and dispatching existing Codex tasks across projects through a lightweight control panel, including scanning task inventories, confirming Continue or Optimize prompts, and tracking dispatch progress.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Start, observe, and interact with Claude Managed Agents from any MCP client — launch an agent, watch its events, reply, approve the tools it wants to run, and stop it. Runs over stdio, HTTP, or AWS Lambda with pluggable auth.

Give AI agents eyes and hands on macOS.

Reliable Codex Desktop automation for long tasks with durable async operations, Plan Mode workflows, and retry-safe task submission.