Which integrations are available for this server?

Integrates with arXiv to browse and summarize research papers from cs.AI, cs.SE, cs.LG, cs.CV, and cs.ML categories. Provides bookmark management for Brave browser, including listing, adding, editing, deleting, and searching bookmarks. Offers comprehensive bookmark management for Firefox, including CRUD, full-text search, deduplication, tag management, age analysis, broken link detection, and JSON/CSV export. Integrates with GitHub to browse trending repositories and issues, enabling AI agents to review repository pages and summarize content. Integrates with Lobsters to browse and summarize trending tech news articles as part of morning briefing routines.

How do I use browser-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@browser-mcp list my Chrome bookmarks" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

browser-mcp

by The-Syntax-Slayer

Overview Schema Related Servers Score Discussions

Python

Local

browser-mcp

CI Build License: MIT PRs Welcome Maintained

Browser automation + bookmark management — over MCP. A unified MCP server for controlling Chrome, Firefox, Edge, and Brave: browse pages, click elements, take screenshots, and manage bookmarks across all major browsers. Ships with a React webapp dashboard.

Features

Browser Automation (Playwright + CDP + CLI)

Tool	Description
`browse_page(url)`	Navigate and extract visible text
`click_element(selector)`	Click elements by CSS selector
`extract_text(selector)`	Extract text from any element
`fill_input(selector, text)`	Type into input fields
`press_key(key)`	Press keyboard keys
`screenshot()`	Viewport PNG screenshot
`browse_url_cli(url, browser)`	Headless CLI mode (no Playwright overhead)
`list_browsers()`	Detect installed browsers and profiles

Bookmark Management (4 Browsers)

17 operations across Chrome, Firefox, Edge, and Brave:

CRUD: list, get, add, edit, delete bookmarks
Search: full-text search by title/URL
Cross-browser sync: migrate bookmarks between any two browsers
Deduplication: find duplicate URLs (Firefox)
Tag management: list, find similar, merge, clean up tags (Firefox)
Age analysis: find old or forgotten bookmarks, get stats (Firefox)
Link checking: detect broken links (Firefox)
Export: bookmarks to JSON/CSV (Firefox)

Bookmarks are read/written directly to the browser's native storage:

Firefox: SQLite (places.sqlite) with brute-force unlock for read-while-running
Chrome/Edge/Brave: Chromium Bookmarks JSON file

Webapp Dashboard (React + Vite)

A full React SPA on port 10781 with:

Dashboard: health status, installed browser detection
Bookmarks panel: list bookmarks by browser with live search

Related MCP server: browser-mcp-server

Quick Start

git clone https://github.com/The-Syntax-Slayer/browser-mcp
cd browser-mcp
just

Opens an interactive recipe dashboard. Otherwise:

# Install dependencies
uv sync

# Install Playwright browsers
playwright install chromium

# Start backend (port 10780)
uv run browser-mcp --serve

# Start frontend (port 10781) — separate terminal
cd webapp && npm install && npm run dev

For more details: INSTALL.md

Tools Reference

Browser Automation

# Navigate and extract
await browse_page("https://example.com")
# → {"title": "...", "text": "...", "url": "...", "status": 200}

# Click and interact
await click_element("button#submit")
await fill_input("#search", "hello world")
await press_key("Enter")

# Screenshot
await screenshot()
# → {"screenshot_b64": "iVBORw0KGgo..."}

# CLI mode (no Playwright session needed)
await browse_url_cli("https://example.com", browser="chrome")

# Detect installed browsers
await list_browsers()
# → {"browsers": {"chrome": {"installed": true, "path": "..."}, ...}}

Bookmark Management

# List bookmarks from Chrome
await browser_bookmarks(operation="list_bookmarks", browser="chrome")

# List from Firefox
await browser_bookmarks(operation="list_bookmarks", browser="firefox")

# Add a bookmark
await browser_bookmarks(
    operation="add_bookmark",
    browser="chrome",
    url="https://example.com",
    title="Example",
)

# Search
await browser_bookmarks(operation="search", browser="firefox", search_query="python")

# Find duplicates (Firefox only)
await browser_bookmarks(operation="find_duplicates", browser="firefox")

# Sync bookmarks from Firefox to Chrome
await browser_bookmarks(
    operation="sync_bookmarks",
    browser="firefox",
    target_browser="chrome",
)

# Export Firefox bookmarks
await browser_bookmarks(operation="export_bookmarks", browser="firefox", export_format="json")

# Find forgotten bookmarks (not visited in 1 year)
await browser_bookmarks(
    operation="find_forgotten_bookmarks",
    browser="firefox",
    age_days=365,
)

Workflow Tools

Tool	Description
`morning_briefing(config_name)`	Configurable daily page routine with 4 built-in profiles
`browse_items(items_json, task)`	Browse a list of links (from aiwatcher/arxiv/gitops) with summaries
`browse_workflow(task, initial_url)`	Multi-step agentic browsing from natural language task

Morning briefing profiles (defined in conf/morning_pages.json):

Profile	Pages	Integrations
`default`	HN + GitHub Trending	AIWatcher, GitHub repos
`dev`	HN + Python Trending + Lobsters	AIWatcher, arXiv cs.AI/cs.SE
`research`	arXiv cs.AI + r/MachineLearning	AIWatcher, arXiv cs.AI/LG/CV/ML
`fleet`	Sandra's repos	AIWatcher, 6 fleet repos

Chaining with fleet MCP servers:

# 1. Get top items from aiwatcher-mcp
items = await aiwatcher.get_top_items(hours=24, limit=5)
# 2. Browse them
await browse_items(items_json=items, task="What's interesting?")

# 1. Get GitHub issues
issues = await gitops.issue_list(owner="The-Syntax-Slayer", repo="browser-mcp")
# 2. Browse the issue pages
await browse_items(items_json=issues)

Full Operation List

Operation	Chrome	Firefox	Edge	Brave
list_bookmarks	✓	✓	✓	✓
get_bookmark	✓	✓	✓	✓
add_bookmark	✓	✓	✓	✓
edit_bookmark	✓	✓	✓	✓
delete_bookmark	✓	✓	✓	✓
search / search_bookmarks	✓	✓	✓	✓
sync_bookmarks	✓	✓	✓	✓
find_duplicates	—	✓	—	—
export_bookmarks	—	✓	—	—
list_tags	—	✓	—	—
find_similar_tags	—	✓	—	—
merge_tags	—	✓	—	—
clean_up_tags	—	✓	—	—
find_old_bookmarks	—	✓	—	—
find_forgotten_bookmarks	—	✓	—	—
get_bookmark_stats	—	✓	—	—
find_broken_links	—	✓	—	—
refresh_bookmarks	—	✓	—	—

Architecture

Browser Control Layers

Layer	Chrome/Chromium	Firefox
Bookmark read/write	Direct JSON file	Direct SQLite
Headless automation	Playwright (primary) + CDP WebSocket	Playwright (primary) + geckodriver
CLI quick ops	`chrome --headless --dump-dom`	`firefox --headless --screenshot`

Ports

Port	Service
10780	Backend (FastAPI + MCP HTTP)
10781	Frontend (Vite React dev server)

Project Structure

browser-mcp/
├── src/browser_mcp/
│   ├── server.py              # MCP tools + browser lifecycle
│   ├── app.py                 # FastAPI app with /health + MCP mount
│   ├── config.py              # Environment-based settings
│   ├── __main__.py            # CLI entry point (stdio / HTTP)
│   └── bookmarks/             # Bookmark management backend
│       ├── portmanteau.py     # Main browser_bookmarks MCP tool
│       ├── firefox_bookmarks.py    # Firefox SQLite backend
│       ├── chromium_common.py      # Chrome/Edge/Brave JSON backend
│       ├── sync.py            # Cross-browser sync
│       └── firefox/           # 13 submodules (db, status, utils, etc.)
├── webapp/                    # React + Vite dashboard (port 10781)
│   ├── src/
│   │   ├── pages/Dashboard.tsx
│   │   └── pages/Bookmarks.tsx
│   └── package.json
└── justfile

Config

Env Var	Default	Description
`BROWSER_MCP_HOST`	127.0.0.1	HTTP bind address
`BROWSER_MCP_PORT`	10780	HTTP backend port
`BROWSER_MCP_FRONTEND_PORT`	10781	Vite frontend port
`BROWSER_HEADLESS`	true	Run Playwright headless
`MCP_TRANSPORT`	—	Set to `http` for HTTP mode

Running

# stdio mode (Claude Desktop, MCP clients)
uv run browser-mcp --stdio

# HTTP mode (web dashboard + API)
uv run browser-mcp --serve

# Debug mode
uv run browser-mcp --serve --debug

Changelog

See CHANGELOG.md.

License

MIT

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

1Releases (12mo)

Commit activity

Resources

GitHub Repository

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