接入你的智能体
从发布者处安装。不是 PlugMCP 端点。
远程 URL 还是本机命令？ 两种安装方式的区别
来自发布者
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.
A unified web extraction and stateful automation engine for AI. Replaces heavy testing frameworks with token-optimized browser control, deep research, and HITL.
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.
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.
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.--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.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.This repository includes captured evidence artifacts that validate extraction and HITL flows against representative protected targets.
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 root). All fields are optional; environment variables act as fallback.
{
"deep_research": {
"enabled": true,
"llm_base_url": "http://localhost:1234/v1",
"llm_api_key": "",
"llm_model": "lfm2-2.6b",
"synthesis_enabled": true,
"synthesis_max_sources": 3,
"synthesis_max_chars_per_source": 800,
"synthesis_max_tokens": 1024
}
}
Recommended operational flow:
memory_search before any new research run — skip live fetching if similarity ≥ 0.60 and skip_live_fetch is true.web_search for URL-only discovery, or web_search(include_content=true) to search and scrape top results in one round-trip.web_fetch(mode="single") with output_format="clean_json", and set query + strict_relevance=true to keep only relevant sections.proxy_control with action:"grab" to refresh the proxy list, then retry with use_proxy:true.visual_scout when auth_risk_score >= 0.4, then use hitl_web_fetch(auth_mode="challenge") for CAPTCHA walls or hitl_web_fetch(auth_mode="auth") for login walls.deep_research handles multi-hop search + scrape + LLM synthesis automatically. Tune depth (1–3) and max_sources per run cost budget.scout_browser_automate with step arrays for tabs, locator assertions, screenshots/PDF, route mocks, file uploads, and browser-state setup. If blocked by first-time login/CAPTCHA, call scout_agent_profile_auth, then resume automation.deep_research with Ollama or qwen3.5 sometimes fail or fall back to heuristic mode?Some reasoning-capable local models return OpenAI-compatible /v1/chat/completions responses with message.reasoning populated but message.content empty. Cortex Scout now retries local Ollama endpoints through native /api/chat with think:false when that pattern is detected.
Recommended config for local 4B-class Ollama models:
llm_api_key: "" in cortex-scout.json is valid and means "no auth required"synthesis_max_sources at 1-2synthesis_max_chars_per_source around 600-1000synthesis_max_tokens around 512-768If you still see slow or unstable synthesis, reduce synthesis_max_sources before increasing token limits.
Each headless request uses a unique temporary profile, so normal scraping and deep_research are safe from profile lock races. Only HITL flows (like hitl_web_fetch) using a real browser profile can hit a lock if you run them concurrently or have Brave/Chrome open on the same profile. To avoid: run HITL calls one at a time, and close all browser windows before reusing a profile.
Checklist:
Check these before anything else:
RUST_LOG=warn, not info.env-style configs, pass the binary path directly after the env assignments. Do not insert "--" in mcp.json args.env; use command plus an env object.See CHANGELOG.md.
MIT. See LICENSE.
A unified web extraction and stateful automation engine for AI. Replaces heavy testing frameworks with token-optimized browser control, deep research, and HITL.
工具
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常见问题
在本页复制适用于 Cursor、Claude Desktop、Claude Code 或 VS Code 的 stdio 配置。它使用发布者的安装方式，而不是 PlugMCP 代理。
此记录未列出必需的环境变量。
Cortex Scout 通过 stdio 在本地运行。
上次检查时间：2026-10-28。 A unified web extraction and stateful automation engine for AI. Replaces heavy testing frameworks with token-optimized browser control, deep research, and HITL.
