Which integrations are available for this server?

Allows searching GitHub repositories, code, and issues with filters for stars, language, and sort order. Provides web search capabilities using SearXNG with 70+ engines, hybrid reranking, and domain filters. Enables structured academic search via Semantic Scholar API, returning citations, DOI, abstract, and open-access PDFs. Allows sending webhook notifications to Telegram when watched pages change.

How do I use argus-web-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@argus-web-mcp search the web for AI trends 2025" 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.

argus-web-mcp

by GifariKemal

Overview Schema Related Servers Score Discussions

Python

Remote

Argus Panoptes - the all-seeing hundred-eyed giant. A self-hosted, unlimited, owned web fetch / scrape / search MCP server for SURIOTA. Mythological sibling to the Hermes AI Server. Every Claude Code / Codex CLI connects over remote HTTP -> zero local process on the client.

Why Argus

We surveyed the 12 leading paid/free web tools. All meter requests, truncate content, or cost money. Argus is built on best-in-class OSS, self-hosted on the SURIOTA VPS - so it's unlimited, free per-request, returns full content (no truncation), and is owned end-to-end. It's tools, not a brain: the consuming agent (Claude Code's Opus 4.8 / Codex) does the reasoning - Argus needs no LLM.

You were paying for...	Argus replaces it with...	Edge
Brave / Tavily / Exa search	`search` / `smart_search` (SearXNG, 70+ engines)	unlimited, multi-engine + semantic rerank
Jina Reader / Firecrawl scrape	`read` / `scrape` / `batch_read` / `crawl`	full content, JS render + stealth, no truncation
Jina / Firecrawl PDF	`read_pdf` (pymupdf4llm + Docling)	tables preserved (COT/FOMC)
Firecrawl extract / map	`extract_structured` / `map_urls`	CSS/XPath, sitemap discovery
Exa findSimilar / answer	`find_similar` / `research(deep)`	local embeddings, full-content bundle
- (no competitor self-hosts)	`github_search` / `scholar_search` / trading extractors / `watch`	structured GitHub / academic / FX moat

Related MCP server: crawl-mcp

Architecture

Fetch strategy (cheap -> expensive): httpx static -> trafilatura -> escalate to Crawl4AI/Playwright only when JS/thin -> Patchright stealth on anti-bot -> Wayback archive if the host is unreachable. Every hop is SSRF-guarded.

The 20 tools

Tool	What it does
`search`	Web search via SearXNG - categories (general/news/science/it), domain filters, safesearch, hybrid lexical+semantic rerank, recency boost, auto-backoff on throttle
`smart_search`	Auto-routes a query (deterministic, no LLM) -> github / scholar / news / it / general
`scholar_search`	Structured academic search (Semantic Scholar -> CrossRef): citations, DOI, abstract, OA-PDF
`github_search`	Structured GitHub `repositories`/`code`/`issues` + stars/language/sort
`map_urls`	Discover a site's URLs (sitemap.xml / robots.txt / 1-hop links)
`find_similar`	Semantically-related pages via local embeddings (Exa-style, no API)

Tool	What it does
`read`	URL -> clean markdown/text/html, no truncation; `extract_media` adds links+images
`scrape`	JS-rendered fetch + screenshot/actions; auto-escalates to Patchright stealth on anti-bot
`batch_read`	Parallel `read` over many URLs, partial-failure tolerant
`read_pdf`	PDF -> markdown + tables (pymupdf4llm; `mode='quality'` -> Docling for scanned/complex)
`crawl`	Crawl4AI BFS deep-crawl, robots-respecting, domain-confined

Tool	What it does
`extract_structured`	Pull fields via CSS/XPath selectors (deterministic); optional LLM tier (`auto`/`llm`)
`research`	One-shot: `deep` (search->full-read top-K->bundle) / `quick` (hits) / `answer` (cited, opt-in LLM); `highlights`=top sentences per source

Tool	What it does
`watch` / `list_watches` / `unwatch`	Poll a page (full or selector) -> POST to a webhook (e.g. Telegram) on change
`forexfactory_calendar`	Economic calendar (FairEconomy JSON) -> Aurix `calendar_client` shape
`cot_report`	CFTC Commitments of Traders, structured
`news_sentiment_feed`	Ranked news + optional sentiment score

Trading parsers are validated to >=99% field accuracy (100% on golden files).

Hard guarantees

SSRF - resolve-then-validate, IP-pin anti-rebinding, scheme allowlist, per-hop redirect re-check, private/metadata/CGNAT deny -> 100% test coverage (hard gate).
No silent truncation - full documents always; the streaming body cap is a DoS guard, not a content cap.
Resilience - content-addressed cache (per-source TTL, stale-serve), per-host courtesy delay + circuit breaker, archive egress-fallback.
Secure deploy - bearer/JWT auth + nginx TLS + fail2ban; runs unprivileged via systemd; secrets via EnvironmentFile.

Quickstart (local)

uv venv --python 3.12 && uv pip install -e ".[dev]"
crawl4ai-setup && crawl4ai-doctor          # one-time Chromium
# optional extras: ".[semantic]" (find_similar/rerank), ".[pdf-quality]" (Docling)

# SearXNG (search backend) - loopback only
cd deploy/searxng && docker compose up -d

python -m argus.server                      # stdio (local dev)
# or HTTP:  uvicorn argus.server:app --host 127.0.0.1 --port 8090

claude mcp add --transport http argus https://argus.<domain>/mcp \
  --header "Authorization: Bearer ${ARGUS_TOKEN}"

[mcp_servers.argus]
url = "https://argus.<domain>/mcp"
bearer_token_env_var = "ARGUS_TOKEN"

Benchmarked

Head-to-head vs Claude Code & Codex native web tools (n=50, identical queries): discovery parity, but Argus wins decisively on content depth (~7,000 words of full content per query vs hits/summaries), freshness, and cost/ownership. Semantic rerank quantified at +27% nDCG on conceptual queries. Full report: benchmark/RESULTS.md.

Repo map

Path	What
`src/argus/`	the package - `server.py` (20 tools), `fetch/`, `extract/`, `security/ssrf.py`, `trading/`, `semantic.py`, `cache.py`, `watch.py`
`docs/`	DESIGN / ROADMAP / TOOL-SPECS / COMPETITIVE-GAP
`benchmark/`	harness + RESULTS + head-to-head
`deploy/`	systemd / nginx / provision.sh / fail2ban / SECURITY-AUDIT / searxng/
`SOUL.md` / `AGENTS.md` / `CHANGELOG.md`	identity / agent guide / history

Status

Feature-complete & validated locally. 20 tools / 526 offline tests (+3 browser, +2 slow) green / SSRF 100% / ruff clean / security-audited (no Critical/High). Deploy to the VPS is gated only on owner inputs (subdomain + DNS, ARGUS_TOKEN, optional SearXNG proxy) - see docs/02-ROADMAP.md.

This server cannot be installed

license - not found

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

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