広告掲載
MCP.so
ログイン

InBrowserMCP Project MCP Server

@LofiSu

リポジトリ

基本情報

カテゴリ

開発者ツール

トランスポート

stdio

作者

LofiSu

InBrowserMCP Project MCP Server について

express框架搭建的mcp-sdk实例

InBrowserMCP Project MCP Server の設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

リポジトリ

InBrowserMCP Project MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is InBrowserMCP Project?

The InBrowserMCP Project implements a system based on the Model Context Protocol (MCP) that allows an AI model to interact with a web browser via a browser extension. It consists of a React frontend, a Node.js MCP server, and a Chrome browser extension that communicate to execute browser actions.

How to use InBrowserMCP Project?

Start the MCP server (cd mcp-server && pnpm dev), load the Browser Extension in Chrome (chrome://extensions/), start the Frontend (cd frontend && pnpm dev), then open the frontend application at http://localhost:5173 to send commands that control the browser.

Key features of InBrowserMCP Project

  • React-based frontend for user interaction with AI
  • Node.js MCP server implementing the MCP specification
  • Chrome browser extension connects via WebSocket
  • Server-Sent Events (SSE) for streaming responses
  • Orchestrates browser navigation, clicks, typing, and content extraction

Use cases of InBrowserMCP Project

  • AI-controlled web browsing for automation
  • Automated form filling and data scraping via browser
  • Testing web pages with AI-driven navigation
  • Building AI assistants that can interact with live websites

よくある質問

1

What components make up the InBrowserMCP Project?

The project has three main parts: a React frontend (port 5173), a Node.js MCP server (port 3000), and a Chrome browser extension (WebSocket port 8081).

2

How does the architecture work?

The frontend sends user commands to the MCP server, which translates them into MCP tool calls. The server sends browser actions to the extension via WebSocket, and the extension executes them and returns results. The server then streams responses back to the frontend via SSE.

3

Does the project include an AI model?

No, an AI model is not explicitly implemented in this project; it is assumed that the frontend or MCP server will interact with an external AI model as part of the system.

4

What are the runtime requirements for running InBrowserMCP Project?

You need Node.js and pnpm for the server and frontend, and Google Chrome to load the browser extension. All communication uses localhost ports 5173, 3000, and 8081.

5

How do I start using InBrowserMCP Project?

Follow the general workflow: start the MCP server, load the extension in Chrome, start the frontend, and open the frontend URL. Detailed instructions are in the respective README files for each component.

コメント

「開発者ツール」の他のコンテンツ

ArtiBot Cloud MCP - Zhijiangyun 智匠云

bofob

ArtiBot Cloud MCP (Zhijiangyun 智匠云) — cloud MCP server for robot manipulation data & GPU workloads. 15 tools: robot fleet management, data collection & video recording, post-processing pipelines, and benchmark evaluation

1

Air Pipe

airpipe

Build, validate, deploy — HTTP APIs, cron jobs, webhooks and MCP tools — from your AI client.

Moxie Docs

Jackalope-Dev

Automated codebase documentation for GitHub: searchable docs, MCP context for AI agents, doc drift detection, and Friday Cleanup PRs.

1

Adgentek Ad Server (AdsMCP)

Adgentek

AdsMCP is the MCP entry point into the Adgentek Ad Server. Call ads_serve with the conversation context and get back a native ad matched to user intent, or no ad when one does not fit. Publishers earn on a CPM basis. Fre

Vibgrate MCP

Vibgrate

Query your team's drift, vulnerability, and migration data from any AI assistant. Vibgrate MCP connects Cursor, Claude, ChatGPT, Windsurf, or VS Code to Vibgrate Cloud: 51 tools for DriftScores, CVEs and EOL runtimes, up

3
広告掲載