Browser Use
Browser agents and stealth cloud browsers for AI: run web tasks, fill forms, extract data.
제작자가 쓴 설명(영어 원문)
Rust MCP stealth scraper: anti-bot search/scrape with CDP fallback + HITL non-robot.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
제작자가 레지스트리에 설치 정보를 올리지 않았어요. 아래 제작자의 README를 확인하세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 GitHub 계정 DevsHero 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(2.3.0)은 9개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요.
같은 카테고리에는: Browser Use, Chrome DevTools MCP, MCP Server Browser
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Browser agents and stealth cloud browsers for AI: run web tasks, fill forms, extract data.
MCP server for Chrome DevTools
MCP server for browser use access
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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.
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.
| 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.
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.
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.
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.--headless=new) using a dedicated isolated profile (~/.cortex-scout/agent_profile). It maintains cookies, localStorage, and session state across tool calls without causing SingletonLock collisions with your active desktop browser.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.| 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.
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.
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 port 5000; override via --port, PORT, or CORTEX_SCOUT_PORT)Health check (HTTP server):
./cortex-scout --port 5000
curl http://localhost:5000/health
Install protoc first. lance-encoding uses Protocol Buffers during the release build, so protoc must be on your PATH.
brew install protobufsudo apt-get install -y protobuf-compilersudo dnf install -y protobuf-compilerBasic build (search, scrape, deep research, memory):
git clone https://github.com/cortex-works/cortex-scout.git
cd 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-mcp
If 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.py
This 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.
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
Create cortex-scout.json in the same directory as the binary (or repository ro
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