Browser Use
by browser-use
Lets AI do web tasks for you, such as filling forms, searching and extracting data, in the maker’s cloud browsers or on your computer.
Computer or cloud★ 120,087MITUpdated 16 days ago
Install
ShadowCrawl
Overview
Description from the maker (original English)
Stealth scraping & search. Bypasses Cloudflare, DataDome & LinkedIn via Cyborg HITL approach.
PopNx MCP’s three pillars
These three are never merged into one score: opinions, measurements and popularity are different things.
- User voiceiNo reviews yetReviews open together with accounts in a later step
- Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
- UsageiNot measured yet★ –
What you can do with it
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
- Connection: Runs in the cloud
- Transport: Streamable HTTP
- Category: Web & browsers
Install
Pick the AI app you use, then copy the settings.
Before you install
- Basic checks: 1 of 1 passed
- Runs on the maker’s server: what you ask it goes through their server.
- The registry lists no key to fill in.
You need
- Runs in the cloudNothing to install; it connects over the internet
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Works in Claude on the web, desktop and mobile:
- Open Settings → Connectors
- Press Add custom connector
- Paste the address below and press Add
- If it asks you to sign in, sign in with the maker
https://shadowcrawl--devshero.run.toolsRun this in your terminal
claude mcp add --transport http shadow-crawl https://shadowcrawl--devshero.run.toolsOr copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"shadow-crawl": {
"url": "https://shadowcrawl--devshero.run.tools"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"shadow-crawl": {
"type": "http",
"url": "https://shadowcrawl--devshero.run.tools"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
ChatGPT connects only to servers on the internet:
- Open ChatGPT on the web → Settings → Connectors (Apps)
- Press Create or Add (some plans need Developer mode under Advanced first)
- Paste the address below, give it a name and save
- If it asks you to sign in, sign in with the maker
https://shadowcrawl--devshero.run.toolsMenu names can differ slightly by plan and over time.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
What it can do
We have not read this server’s tool list yet; we check endpoints in rotation.
Basic checksi
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
- ✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account DevsHero, which owns the repo
- … Not checked yet
Still maintained
We have not read this repo from GitHub yet
- … Not checked yet
Has a licence
We have not read this repo from GitHub yet
- … Not checked yet
Endpoint responds
Not checked yet; we check endpoints in rotation
- … Not checked yet
Sign-in with OAuth
Not checked yet; we check endpoints in rotation
- … Not checked yet
No hidden instructions in tool descriptions
Not checked yet; we read the tool list when we check the endpoint
Compared with others in Web & browsersi
- More stars than 0% of the other 876 servers in this category
- Published to the registry more recently than 2% of the other 876 servers in this category
- Basic checks equal to or better than 100% of the other 876 servers in this category
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
Common questions
Is ShadowCrawl safe?
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
What keys or codes does it need?
The registry does not list a required key, though some servers ask you to sign in on first use.
Does it run on my computer or in the cloud?
It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.
Is it still maintained?
The GitHub repo last changed –, and the latest version (2.0.0-rc) reached the registry 9 months ago.
Which apps can use it?
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
What can I use instead?
In the same category: Browser Use, Chrome DevTools MCP, MCP Server Browser
Alternatives
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Chrome DevTools MCP
by ChromeDevTools
Lets AI use Chrome’s developer tools to inspect pages, find what makes them slow and spot errors. Made by the Chrome DevTools team.
Runs on your computer★ 54,821Apache-2.0Updated 15 days ago
Install
MCP Server Browser
by bytedance
MCP server for browser use access
Runs on your computer★ 39,550Apache-2.0Updated 14 months ago
Install
README from the maker
Open the README
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
CortexScout (cortex-scout) — Search and Web Extraction Engine for AI Agents
CortexScout is the Deep Research & Web Extraction module within the Cortex-Works ecosystem.
Designed for agent workloads that require token-efficient web retrieval, reliable anti-bot handling, and optional Human-in-the-Loop (HITL) fallback.
Overview
CortexScout provides a single, self-hostable Rust binary that exposes search, extraction, and stateful browser automation capabilities over MCP (stdio) and an optional HTTP server. Output formats are structured and optimized for downstream LLM use.
It is built to handle the practical failure modes of web retrieval (rate limits, bot challenges, JavaScript-heavy pages) through progressive fallbacks: native retrieval → Chromium CDP rendering → Stateful E2E Testing → HITL workflows.
Tools (Capability Roster)
| Area | MCP Tools / Capabilities | ||
|---|---|---|---|
| Search | web_search (URL discovery) or web_search(include_content=true) (search+content in one call) | ||
| Fetch and Crawl | `web_fetch(mode="single" | "batch" | "crawl")` (unified fetch family) |
| Extraction | extract_fields (primary structured extraction) | ||
| Automation | scout_browser_automate / browser_automate (stateful omni-tool), scout_agent_profile_auth, scout_browser_close | ||
| Anti-bot handling | CDP rendering, proxy rotation, block-aware retries | ||
| HITL | visual_scout, `hitl_web_fetch(auth_mode="challenge" | "auth")` | |
| Memory | memory_search (LanceDB-backed research history) | ||
| Deep research | deep_research (multi-hop search + scrape + synthesis) |
Legacy names remain callable as compatibility aliases (web_search_json, web_fetch_batch, web_crawl, fetch_then_extract, human_auth_session). Agents should prefer the unified primary tools above.
Ecosystem Integration
While CortexScout runs as a standalone tool today, it is designed to integrate with CortexDB and CortexStudio for multi-agent scaling, shared retrieval artifacts, and centralized governance.
🎭 The "Playwright Killer" (Stateful Browser Automation)
CortexScout includes a built-in, stateful CDP automation engine designed specifically for AI Agents, completely replacing heavy frameworks like Playwright or Cypress for E2E testing workflows.
- The Silent Omni-Tool (`scout_browser_automate`): Instead of calling dozens of browser tools, agents pass one array of
steps. The runtime now covers Playwright-style action families in one call: navigation, hover/click/type/wait, locator-driven actions, assertions, tabs, screenshots/PDF, file upload, form fill, dialog policy, coordinate mouse actions, route mocking, console/network capture, and cookie/storage CRUD. - Persistent Agent Profile: Automation runs silently in the background (
--headless=new) using a dedicated isolated profile (~/.cortex-scout/agent_profile). It maintains cookies, localStorage, and session state across tool calls without causingSingletonLockcollisions with your active desktop browser. - QA Mock, Trace, And Verification Engine: Agents can install route mocks (
mock_api,route_list,unroute) with response header overrides/stripping, trace flows (trace_start,trace_stop,trace_export), capture console/network logs, checkpoint browser state, and run both CSS and locator-based assertions plus Playwright-style verification helpers. - The Agent Auth Portal (`scout_agent_profile_auth`): If the silent agent encounters a CAPTCHA or complex OAuth login (like Google/Microsoft) on a new domain, this tool launches the agent's profile in a visible window. You solve the CAPTCHA once, the cookies are saved, and the agent returns to silent automation forever.
Playwright-Style Coverage Map
| Capability Area | Cortex Scout Actions |
|---|---|
| Navigation and input | navigate, navigate_back, click, hover, type, press_key, scroll, wait_for, wait_for_selector, wait_for_locator |
| Locator and verification | click_locator, type_locator, assert, assert_locator, generate_locator, verify_element_visible, verify_text_visible, verify_list_visible, verify_value |
| Tabs and media | tabs, resize, screenshot, snapshot, pdf_save, file_upload, fill_form, handle_dialog |
| Network and mocks | network_tap, network_dump, network_state_set, mock_api, route_list, unroute |
| Browser state | storage_clear, storage_state_export, storage_state_import, storage_checkpoint, storage_rollback, cookie_*, localstorage_*, sessionstorage_* |
| Low-level pointer control | mouse_click_xy, mouse_down, mouse_move_xy, mouse_drag_xy, mouse_up, mouse_wheel |
The main tradeoff versus raw Playwright MCP is packaging, not capability shape: Cortex Scout keeps the browser surface inside one stateful omni-tool so agents spend fewer turns and fewer tokens coordinating multi-step flows.
Anti-Bot Efficacy & Validation
This repository includes captured evidence artifacts that validate extraction and HITL flows against representative protected targets.
| Target | Protection | Evidence | Notes |
|---|---|---|---|
| Cloudflare + Auth | JSON · Snippet | Auth-gated listings extraction | |
| Ticketmaster | Cloudflare Turnstile | JSON · Snippet | Challenge-handled extraction |
| Airbnb | DataDome | JSON · Snippet | Large result sets under bot controls |
| Upwork | reCAPTCHA | JSON · Snippet | Protected listings retrieval |
| Amazon | AWS Shield | JSON · Snippet | Search result extraction |
| nowsecure.nl | Cloudflare | JSON | Manual return path validated |
See proof/README.md for methodology and raw outputs.
Quick Start
Option A — Prebuilt binaries
Download the latest release assets from GitHub Releases and run one of:
cortex-scout-mcp— MCP stdio server (recommended for VS Code / Cursor / Claude Desktop)cortex-scout— optional HTTP server (default port5000; override via--port,PORT, orCORTEX_SCOUT_PORT)
Health check (HTTP server):
./cortex-scout --port 5000curl http://localhost:5000/health
Option B — Build from source
Install protoc first. lance-encoding uses Protocol Buffers during the release build, so protoc must be on your PATH.
- macOS:
brew install protobuf - Ubuntu/Debian:
sudo apt-get install -y protobuf-compiler - Fedora:
sudo dnf install -y protobuf-compiler
Basic build (search, scrape, deep research, memory):
git clone https://github.com/cortex-works/cortex-scout.gitcd cortex-scout cargo build --release --manifest-path mcp-server/Cargo.toml --bin cortex-scout-mcp
This works from the repository root because the manifest path is explicit.
Full build (includes hitl_web_fetch / visible-browser HITL):
cargo build --release --manifest-path mcp-server/Cargo.toml --all-features --bin cortex-scout-mcpIf you also want the optional HTTP server binary, build it explicitly with cargo build --release --bin cortex-scout.
Local MCP smoke test:
python3 publish/ci/smoke_mcp.pyThis runs a newline-delimited JSON-RPC stdio session against the local cortex-scout-mcp binary and exercises the main public tools with safe example inputs.
MCP Integration (VS Code / Cursor / Claude Desktop)
Add a server entry to your MCP config.
VS Code (mcp.json — global, or settings.json under mcp.servers):
The hard timeout guard vars below are required in MCP configs. They are the safety rail that prevents a bad page, stalled browser launch, or stuck scrape stage from holding the whole MCP session open indefinitely.
// mcp.json (global): top-level key is "servers"// settings.json (workspace): use "mcp.servers" instead { "servers": { "cortex-scout": { "type": "stdio", "command": "env", "args": [ "RUST_LOG=warn", "CORTEX_SCOUT_TOOL_TIMEOUT_SECS=90", "CORTEX_SCOUT_TOOL_TIMEOUT_SECS_SCRAPE_URL=90", "CORTEX_SCOUT_TOOL_TIMEOUT_SECS_SEARCH_STRUCTURED=120", "CORTEX_SCOUT_TOOL_TIMEOUT_SECS_VISUAL_SCOUT=45", "CORTEX_SCOUT_BROWSER_LAUNCH_TIMEOUT_SECS=12", "CORTEX_SCOUT_BROWSER_TAB_PROBE_TIMEOUT_SECS=4", "CORTEX_SCOUT_SCRAPE_STAGE_TIMEOUT_SECS=20", "CORTEX_SCOUT_SCRAPE_STAGE_TIMEOUT_SECS_CDP_INITIAL_ATTEMPT=25", "CORTEX_SCOUT_SCRAPE_STAGE_TIMEOUT_SECS_CDP_RETRY_ATTEMPT=25", "CORTEX_SCOUT_SCRAPE_STAGE_TIMEOUT_SECS_FORCED_CDP_ATTEMPT=25", "CORTEX_SCOUT_SCRAPE_STAGE_TIMEOUT_SECS_NATIVE_CDP_FALLBACK=25", "SEARCH_ENGINES=google,bing,duckduckgo,brave", "LANCEDB_URI=/YOUR_PATH/cortex-scout/lancedb", "HTTP_TIMEOUT_SECS=30", "MAX_CONTENT_CHARS=10000", "/YOUR_PATH/cortex-scout/mcp-server/target/release/cortex-scout-mcp" ] } } }
Default behavior is direct/no-proxy. Add IP_LIST_PATH and PROXY_SOURCE_PATH only if you want proxy tools available. If you want proxy_control available without routing normal traffic through proxies, point IP_LIST_PATH at an empty ip.txt file and let agents populate it on demand.
Important: Always use
RUST_LOG=warn, notinfo. Atinfolevel, the server emits hundreds of log lines per request to stderr, which can confuse MCP clients that monitor stderr.
Windows: Windows has no
envcommand. Use thecommand+envobject format instead — see docs/IDE_SETUP.md.
With deep research (LLM synthesis via OpenRouter / any OpenAI-compatible API):
{"servers": { "cortex-scout": { "type": "stdio", "command": "env", "args": [ "RUST_LOG=warn", "CORTEX_SCOUT_TOOL_TIMEOUT_SECS=90", "CORTEX_SCOUT_TOOL_TIMEOUT_SECS_SCRAPE_URL=90", "CORTEX_SCOUT_TOOL_TIMEOUT_SECS_SEARCH_STRUCTURED=120", "CORTEX_SCOUT_TOOL_TIMEOUT_SECS_VISUAL_SCOUT=45", "CORTEX_SCOUT_BROWSER_LAUNCH_TIMEOUT_SECS=12", "CORTEX_SCOUT_BROWSER_TAB_PROBE_TIMEOUT_SECS=4", "CORTEX_SCOUT_SCRAPE_STAGE_TIMEOUT_SECS=20", "CORTEX_SCOUT_SCRAPE_STAGE_TIMEOUT_SECS_CDP_INITIAL_ATTEMPT=25", "CORTEX_SCOUT_SCRAPE_STAGE_TIMEOUT_SECS_CDP_RETRY_ATTEMPT=25", "CORTEX_SCOUT_SCRAPE_STAGE_TIMEOUT_SECS_FORCED_CDP_ATTEMPT=25", "CORTEX_SCOUT_SCRAPE_STAGE_TIMEOUT_SECS_NATIVE_CDP_FALLBACK=25", "SEARCH_ENGINES=google,bing,duckduckgo,brave", "LANCEDB_URI=/YOUR_PATH/cortex-scout/lancedb", "HTTP_TIMEOUT_SECS=30", "MAX_CONTENT_CHARS=10000", "OPENAI_BASE_URL=https://openrouter.ai/api/v1", "OPENAI_API_KEY=sk-or-v1-...", "DEEP_RESEARCH_LLM_MODEL=moonshotai/kimi-k2.5", "DEEP_RESEARCH_ENABLED=1", "DEEP_RESEARCH_SYNTHESIS=1", "DEEP_RESEARCH_SYNTHESIS_MAX_TOKENS=4096", "/YOUR_PATH/cortex-scout/mcp-server/target/release/cortex-scout-mcp" ] } } }
Multi-IDE guide: docs/IDE_SETUP.md
Configuration (cortex-scout.json)
Create cortex-scout.json in the same directory as the binary (or repository ro
Only the beginning is shown; read the rest in the repo