Konnect

Konnect

Bridges AI agents to a real browser using a persistent daemon and Chrome extension for driving actual login sessions, cookies, and tabs.

Category
Visit Server

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.
  • evaluate runs in the MAIN world for trusted local use only. Sites that check event.isTrusted may reject synthetic events — a product boundary, not a bug.

License

MIT. Clean-room implementation; see ARCHITECTURE.md.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured