Scout MCP Server
OfficialClick on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Scout MCP Server Search the web for the latest on the EU AI Act and summarize the top 5 sources."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Scout MCP Server
Give your coding agent the live web. Scout's MCP server adds web search, scraping to Markdown, structured extraction, crawling, screenshots, and company lookup as tools any MCP client can call: Claude Code, Codex, Gemini CLI, Antigravity, Cursor, Windsurf, and Claude Desktop.
It has zero dependencies — the MCP protocol is implemented in a few hundred lines of plain JavaScript, with no build step and nothing pulled from npm at install time. When you run it, the only code that runs is the code in this repo. See SECURITY.md.
Tools
Tool | What it does |
| Search the live web; ranked results as JSON. |
| Fetch a page as clean, LLM-ready Markdown (handles JS + bot defenses). |
| Pull structured data from one or more URLs against an objective. |
| Crawl a site from a start URL, bounded by |
| Capture a page screenshot. |
| Company profile from a domain (name, industry, socials, logo). |
| Answer a question by reading a page and the pages it links to. |
| Build a list of entities matching a natural-language query. |
Related MCP server: searxNcrawl
Get a key
Create an API key at platform.usescout.sh/settings and set it as SCOUT_API_KEY. Every example below uses npx, so there's nothing to install first.
Install per client
Claude Code
claude mcp add scout --env SCOUT_API_KEY=sk_your_key -- npx -y @scout-ai/mcpCodex CLI
Add to ~/.codex/config.toml:
[mcp_servers.scout]
command = "npx"
args = ["-y", "@scout-ai/mcp"]
env = { SCOUT_API_KEY = "sk_your_key" }Gemini CLI
Add to ~/.gemini/settings.json:
{
"mcpServers": {
"scout": {
"command": "npx",
"args": ["-y", "@scout-ai/mcp"],
"env": { "SCOUT_API_KEY": "sk_your_key" }
}
}
}Antigravity
In the MCP settings, add a server with this config (or paste it into the MCP config file):
{
"mcpServers": {
"scout": {
"command": "npx",
"args": ["-y", "@scout-ai/mcp"],
"env": { "SCOUT_API_KEY": "sk_your_key" }
}
}
}Cursor
Add to .cursor/mcp.json (project) or ~/.cursor/mcp.json (global):
{
"mcpServers": {
"scout": {
"command": "npx",
"args": ["-y", "@scout-ai/mcp"],
"env": { "SCOUT_API_KEY": "sk_your_key" }
}
}
}Windsurf
Add to ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": {
"scout": {
"command": "npx",
"args": ["-y", "@scout-ai/mcp"],
"env": { "SCOUT_API_KEY": "sk_your_key" }
}
}
}Claude Desktop
Add to claude_desktop_config.json (Settings → Developer → Edit Config) using the same mcpServers block as above.
Use it
Once connected, ask your agent things like:
"Search the web for the latest on the EU AI Act and summarize the top 5 sources."
"Scrape https://example.com/pricing and pull the plan names and prices."
"Look up stripe.com and tell me their industry and socials."
The agent picks the right Scout tool and calls it.
Progress on long jobs
scout_search with depth: "deep" runs an agentic multi-step search server-side. The server streams Scout's run events and forwards them as MCP progress notifications, so clients that show progress (Claude Code, Cursor) display live updates instead of a frozen spinner. The final results come back when the run finishes.
Hosted HTTP/SSE transport
Besides stdio, the server can run over HTTP using MCP's Streamable HTTP transport, so a remote client can connect by URL:
SCOUT_API_KEY=sk_your_key npx -y -p @scout-ai/mcp scout-mcp-http
# listening on :3000/mcpVariable | Default | Purpose |
|
| Listen port. |
|
| Endpoint path. |
| (none) | If set, clients must send |
Point an MCP client at http://your-host:3000/mcp. There's a /health endpoint for load balancers. Each request is stateless (a fresh server per request), which keeps it simple to run behind any HTTP front end.
Configuration
Variable | Default | Purpose |
| (required) | Your Scout API key. |
|
| Override the API origin. |
Run from source
No install, no build (zero dependencies):
SCOUT_API_KEY=sk_your_key node bin/scout-mcp.js # stdio
SCOUT_API_KEY=sk_your_key node bin/scout-mcp-http.js # hosted HTTP/SSE
node test/smoke.mjs # run the protocol testLicense
Available Tools
8 toolsscout_answerA
Answer a natural-language question by reading a page and the pages it links to.
Inputs: url (required), question (required).
scout_companyA
Look up a company profile from its domain: name, description, industry, socials, logo, and more.
Inputs: domain (required).
scout_crawlC
Crawl a website from a start URL and return its pages. Bound it with max_pages.
Inputs: start_url (required), max_pages, same_host_only.
scout_extractB
Extract structured data from one or more URLs. Provide an objective describing what to pull.
Inputs: urls (required), objective.
scout_find_allA
Build a list of entities matching a natural-language query (e.g. "Series A fintech companies in Europe").
Inputs: query (required), limit.
scout_scrapeC
Fetch a web page and return clean, LLM-ready Markdown. Handles JS rendering and bot defenses.
Inputs: url (required), max_chars.
scout_screenshotB
Capture a screenshot of a web page. Returns a URL (or data URI) to the image.
Inputs: url (required), full_page.
scout_searchA
Search the live web and return ranked results as JSON. Set depth="deep" for an agentic multi-step search; it reports progress as it runs.
Inputs: query (required), limit, country, depth.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 8 tools
Each tool has a distinct purpose: search, scrape, crawl, extract, screenshot, company lookup, entity building, and question answering. Overlaps are minimal and clarified by descriptions.
All tools follow the consistent pattern 'scout_verb' with snake_case, making it easy to predict tool names.
8 tools is well-scoped for a web research server, covering common operations without being overwhelming.
The set covers core web research needs: search, scrape, crawl, extract, screenshot, company lookup, and intelligent querying. No obvious gaps.
Maintenance
Related MCP Connectors
Web scraping, search, crawling, structured extraction and research for AI agents.
Web data for agents. Extract web pages, crawl websites, discover URLs, and search the web.
Web data for agents: YouTube transcripts, screenshots, Google News, WHOIS, jobs, tech stack, more.
Web infrastructure for AI agents: scrape, crawl and search the web, run browsers and agents.
Related MCP Servers
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to perform live web searches with ranked results and extracted page passages, plus clean markdown extraction of any URL.MIT
- FlicenseNot gradedqualityAmaintenanceEnables AI agents to run web searches across configured providers and crawl individual pages or entire sites into deduplicated Markdown or JSON, including options for authenticated pages and CLI/API access.-
- FlicenseNot gradedqualityAmaintenanceEnables AI agents to search the web across configured providers and crawl individual pages or entire sites into clean, deduplicated Markdown or JSON.-
- FlicenseNot gradedqualityAmaintenanceEnables AI agents to search the web through configured providers and crawl pages or whole sites into clean, deduplicated Markdown or JSON, including authenticated crawls.-