"Web Browser Named Chrome or Related Uses of Chrome" matching MCP servers:

Lets several AI clients drive one shared, signed-in Chrome at the same time, giving each session its own background tabs and tab group with per-tab leases so mutations queue while reads overlap. Exposes a full Chrome DevTools-style toolset plus Claude's 31-member browser toolset, along with an HTTP endpoint that turns Messages API tool_use blocks into tool_result blocks.

An MCP server that connects AI agents to a running Chrome tab via the Chrome DevTools Protocol (CDP), enabling runtime debugging and page inspection.

Enables AI coding assistants to control and inspect a live Chrome browser for automation, debugging, performance analysis, and screenshot capture through Chrome DevTools.

Lets coding agents control and inspect a live Chrome browser via the Model-Context-Protocol, providing advanced browser debugging, performance insights, and reliable automation.

Enables MCP clients to drive individually named Chrome profiles, providing tools for tabs, navigation, page interaction, screenshots, JavaScript evaluation, console logs, and network inspection over stdio without a TCP port.

Enables AI assistants to inspect Chrome Web Store status, metrics, ratings, and reviews, and to upload, publish, roll back, or adjust rollout of extension versions, with human confirmation for changes that affect users.

Enables AI coding agents to control and inspect a live Chrome browser for reliable automation, in-depth debugging, performance analysis, and high-speed batched or parallel workflows.

Lets coding agents control and inspect a live Chrome browser for reliable automation, in-depth debugging, and performance analysis. Provides access to Chrome DevTools capabilities such as tracing, network inspection, screenshots, and console messages through MCP clients.

Lets coding agents control and inspect a live Chrome browser via MCP, providing Chrome DevTools capabilities for automation, debugging, and performance analysis.

Enables AI agents to attach to Chrome tabs, set breakpoints, inspect scope variables, evaluate expressions, and step through code using Chrome DevTools Protocol for runtime debugging.

Rust-based MCP server that lets AI agents natively control and debug Chromium browsers via the Chrome DevTools Protocol (CDP). Single pre-compiled binary, installable with npx @raultov/chrome-debug-mcp, Homebrew or one shell command — no Rust toolchain.

Enables AI to interact with Chrome DevTools Protocol to inspect and debug live web pages, including DOM, styles, console logs, and network requests.

Enables AI coding agents to inspect and operate Chrome as a developer, including reading DevTools console/network data, evaluating JavaScript, and managing unpacked extensions during an edit-test-debug loop.

Enables MCP clients like Claude Desktop to automate and interact with claude.ai via a Chrome extension and WebSocket relay.

An MCP Server for Chrome DevTools, following the Chrome DevTools Protocol. Integrates with Claude Desktop and Claude Code.

Enables agents to read Chrome Web Store metrics for an extension—installs, uninstalls, active users, impressions, and page views—with optional breakdowns and date ranges. Access is read-only and requires your own Google Cloud app credentials.

Provides comprehensive Chrome browser debugging capabilities including DOM inspection, network monitoring, console logs, JavaScript execution, breakpoint debugging, and screenshot capture for AI-assisted frontend development.

A fork of Chrome DevTools MCP that adds Streamable HTTP transport for multiple AI agents to concurrently control and inspect a live Chrome browser via the Model Context Protocol.

Enables coding agents to control and inspect a live Chrome browser, providing reliable automation, debugging, performance insights, screenshots, network analysis, and console messages through MCP.

A token-optimized MCP server that groups Chrome Devtools tools into 8 semantic operations, reducing context window tokens by 69.5% while preserving full functionality.

Enables any MCP client to drive the user's real Chrome profile through a Chrome extension bridge, with tools for navigation, accessibility snapshots, ref-based interactions, console/network reading, screenshots, tab management, and restricted script evaluation.

Enables coding agents to control and inspect a live Chrome browser for reliable automation, in-depth debugging, and performance analysis.

Enables AI coding agents to control and inspect a live Chrome browser via MCP, including performance tracing, network and console debugging, screenshots, and reliable Puppeteer-based automation.

Gives an agent a real, watchable Chrome window to open and read pages, click and type, take screenshots, and inspect console messages, network requests, and script output. It also records performance traces and runs Lighthouse audits, with each chat getting its own browser that closes when the chat ends.

Enables multiple MCP clients to share a single Chrome instance while maintaining isolated tab sessions for each client. It acts as a multiplexer between clients and the chrome-devtools-mcp server, preventing tab conflicts across different sessions like Claude Code windows.

Enables OpenCode to control a real browser through a local extension bridge, supporting navigation, DOM reading, clicking, typing, form filling, scrolling, dragging, screenshots, and more.

MCP server that lets AI coding tools control and observe a running Node.js process through the chrome devtools protocol (CDP), via a lightweight Debug Adapter Protocol (DAP) bridge.

A Model Context Protocol (MCP) server implementation that provides seamless integration between Chrome bookmarks and AI assistants. This server enables AI models to access, search, analyze, and manage Chrome bookmarks through a standardized protocol.

Shares one Chrome browser across multiple AI coding sessions via an MCP proxy, adding lifecycle management, tool filtering, and anti-detection while wrapping the upstream chrome-devtools-mcp server.

Enables MCP clients to drive your already-open Chrome browser like a human, using 45 tools for navigation, perception, capture, and trusted input that pages receive as genuinely user-generated.