Konnect
Bridges AI agents to a real browser using a persistent daemon and Chrome extension for driving actual login sessions, cookies, and tabs.
README
Konnect
A local browser-automation bridge that lets AI agents drive your real browser — your actual login sessions, cookies, and tabs — instead of a cloud sandbox or headless instance. Konnect connects MCP-compatible coding agents (and a token-cheap CLI) to Comet Browser via a long-lived daemon and a Chrome MV3 extension.
Status: production. Runs on macOS via launchd (port 9223).
Architecture
A persistent aiohttp daemon (daemon/, listens on :9223) owns the WebSocket to
a Chrome MV3 extension (extension/) that performs the actual page interaction;
the WS survives MV3 service-worker eviction via an offscreen document. Two thin
clients front the daemon's HTTP API: an MCP stdio shim (mcp/) for AI agents and
a CLI (cli/) for low-token coding. The daemon is the single source of truth —
MCP is one client, not the only interface.
See ARCHITECTURE.md for full design rationale and the
decision tree (why daemon-over-MCP, why snapshot-first, why CLI+SKILL alongside MCP).
Components
konnect/
├── daemon/ # aiohttp daemon: /command /ws /health (the persistent core)
├── extension/ # Chrome MV3 extension (service worker + content script + offscreen WS)
├── mcp/ # MCP stdio server — thin shim → daemon HTTP
├── cli/ # argparse CLI → daemon HTTP (token-cheap)
├── skill/ # SKILL.md — agent operating instructions
├── tests/ # isolated test harness (disposable Chromium + CDP)
├── deploy/ # launchd plist template + install.sh
└── docs/ # operations notes
Install
# 1. Python deps (aiohttp for the daemon)
pip install -e .
# 2. Install + start the daemon under launchd
deploy/install.sh
# 3. Load the extension (one-time, manual)
# chrome://extensions (or comet://extensions) → Developer mode → Load unpacked
# → choose this repo's extension/ directory
deploy/install.sh auto-detects a Python with aiohttp (or takes an explicit
path: deploy/install.sh /path/to/python). It renders local.konnect.daemon.plist
with your $HOME and repo path — no hardcoded user paths.
Verify the daemon sees the extension:
curl http://127.0.0.1:9223/health # → {"extension_connected": true}
Logs: /tmp/konnect-daemon.log. Stop: launchctl unload ~/Library/LaunchAgents/local.konnect.daemon.plist.
Usage — MCP tools
Wire mcp/konnect_mcp.py as an MCP server in your agent (Claude, Cursor, opencode).
Exposed tools (all proxy to the daemon over HTTP):
| Tool | Purpose |
|---|---|
konnect_health |
Check daemon + extension connection |
konnect_list_tabs |
List open browser tabs (group + blocked state) |
konnect_find_tab |
Select an already-open tab by URL prefix |
konnect_navigate |
Open a URL (new background tab by default) |
konnect_snapshot |
AX-style accessibility tree with ref=N targeting |
konnect_click |
Click an element by ref |
konnect_fill |
Fill an input/textarea/select/contenteditable by ref |
konnect_screenshot |
Capture tab/element to a PNG file (read via Read) |
konnect_get_text |
Visible text of the current tab |
konnect_evaluate |
Run JS in the page main world (fallback for ref limits) |
Targeting is snapshot-first: call konnect_snapshot, read the ref=N tags, then
konnect_click/konnect_fill by ref. Screenshots write to disk and are read with
Read — never base64 into context.
Security
- Bearer-token auth (
extension/token.json), generated by the daemon; tokens are git-ignored and never committed. evaluateruns in the MAIN world for trusted local use only. Sites that checkevent.isTrustedmay reject synthetic events — a product boundary, not a bug.
License
MIT. Clean-room implementation; see ARCHITECTURE.md.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。