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  3. Argus
Argus logo
Health: ActiveRecent health check succeeded.Last checked 9/9/2026, 4:05:03 PM

Argus

User RatingsBe the first to rate and review this MCP server!
View Repository5 GitHub StarsTotal stargazers on GitHub for the source repository (5 stars).Visit Website

Multi-provider search broker with fallback, ranking, content extraction, and budget control via one API.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag โ€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON โ–พ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "khamel83-argus": {
      "command": "uvx",
      "args": [
        "argus-search"
      ]
    }
  }
}

๐Ÿ’ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives๐Ÿ”Ž More in Search & Data Extraction

Overview

Argus is a retrieval platform that routes search queries across 14 providers with automatic fallback and budget enforcement. It performs multi-step content extraction to return full page text, recovers dead URLs, and builds local research packs with traceable artifacts. Argus supports multi-turn sessions for conversational context and offers multiple integration paths including HTTP API, CLI, MCP server, and Python SDK. It is suitable for AI agents, retrieval-augmented generation pipelines, and operations teams needing reliable search and local evidence capture.

Use cases

โ€ขRoute search queries across multiple providers with automatic fallback
โ€ขExtract and capture important content from web pages
โ€ขRecover dead or archived URLs using Wayback Machine and archives
โ€ขBuild local document and research packs with traceable data
โ€ขIntegrate search and extraction into AI agents or RAG pipelines

Key features

โ€ขTopology-aware search routing based on network type
โ€ขSupports 14 search providers with free-first tier and budget skipping
โ€ข12-step content extraction returning full page text with quality gates
โ€ขMulti-turn session support for conversational search context
โ€ขDead URL recovery via archive fallbacks
โ€ขMultiple integration modes: HTTP API, CLI, MCP server, Python SDK

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Argus.

Extracted Tool Capabilities
Topology-aware search routing based on network type
Supports 14 search providers with free-first tier and budget skipping
12-step content extraction returning full page text with quality gates
Multi-turn session support for conversational search context
Dead URL recovery via archive fallbacks
Multiple integration modes: HTTP API, CLI, MCP server, Python SDK

Documentation Overview

Argus

Python 3.11+ PyPI Version PyPI Downloads License: MIT CI MCP Registry Docker

Retrieval platform for AI agents. Argus routes search across 14 providers, recovers dead URLs, captures important site content, builds local docs-plus-research packs, and persists everything with traceable local artifacts.

Features at a glance:

  • Topology-aware acquisition โ€” Argus knows if it's on a residential IP or datacenter, routing search and extraction automatically to avoid blocks and minimize network hops.
  • 14 providers, one API โ€” free-first tier routing, budget-exhausted providers skipped automatically
  • Zero-key start โ€” pip install argus-search gives you DuckDuckGo + Yahoo immediately, no accounts needed
  • SearXNG self-host = 70+ engines โ€” Google, Bing, Yahoo, Startpage, Ecosia, Qwant and more via one Docker container
  • 12-step content extraction โ€” returns full page text with quality gates, not just links
  • Opinionated retrieval workflows โ€” recover dead articles, capture important pages from a site, and build local docs-plus-research packs
  • Argus-owned corpus storage โ€” runtime data goes to a writable user data directory, not your repo checkout
  • Multi-turn sessions โ€” pass session_id for conversational context across searches
  • Score attribution โ€” optionally show which providers contributed to each fused RRF score
  • Usage dashboard โ€” inspect provider budgets, recent query volume, and machine-level usage at /dashboard
  • 4 search modes โ€” discovery, research, recovery, grounding
  • Dead URL recovery โ€” /recover-url with Wayback Machine and archive fallbacks
  • 4 integration paths โ€” HTTP API, CLI, MCP server, Python SDK

Built for AI agent builders, RAG pipelines, and ops teams who need reliable search, capture, and local evidence without stitching APIs together.

Status: beta. The retrieval workflows and corpus model are production-oriented, but still maturing.

Status: see the public status page. Authorized maintainers can use the private argus-ops README for the latest dated reports.

Current production checkpoint โ€” September 7, 2026: The authenticated HTTP API and MCP adapter are operational, and sampled free search works through SearXNG, Yahoo, and GitHub. DuckDuckGo is intermittent and fails closed after acquisition-policy blocks. Production readiness is ready=true, degraded; paid providers are not currently admitted until their non-secret credential-version and account-scope bindings are recorded. Browser capability and recovery metadata evidence remain open. See the current status matrix before relying on a provider.

Contents

  • Quickstart
  • Development
  • Where Argus Writes Data
  • Opinionated Workflows
  • Providers
  • HTTP API
  • Dashboard
  • Integration
    • CLI
    • MCP
    • Python
  • Content Extraction
  • Architecture
  • Configuration
  • When Not To Use Argus
  • FAQ

Quickstart

Mode 1: Local CLI (zero config)

Terminal
pip install argus-search && argus search -q "python web frameworks"

That's it. DuckDuckGo handles the search โ€” no accounts, no keys, no containers. You get unlimited free search from your laptop right now. Add API keys whenever you want more providers, or don't.

bash
argus extract -u "https://example.com/article"       # extract clean text from any URL
argus recover-article -u "https://example.com/dead-post"
argus capture-site -u "https://docs.example.com"
argus build-research-pack -t "example sdk" --official-url "https://docs.example.com"

Works on any machine with Python 3.11+ โ€” laptop, Mac Mini, Raspberry Pi, cloud VM. Nothing to host.

For MCP (Claude Code, Codex, OpenCode, Cursor, VS Code):

server.ts
pipx install argus-search[mcp]
export ARGUS_MCP_STANDALONE=true  # explicit development-only local broker
argus mcp init --global --client all

That writes native config for Claude Code, Codex CLI, OpenCode, and Cursor. Restart the client after configuration. For manual stdio setup:

config.json
{"mcpServers": {"argus": {"command": "argus", "args": ["mcp", "serve"], "env": {"ARGUS_MCP_STANDALONE": "true"}}}}

Or install from the MCP Registry:

config.json
{
  "mcpServers": {
    "argus": {
      "registryType": "pypi",
      "identifier": "argus-search",
      "runtimeHint": "uvx",
      "env": {"ARGUS_MCP_STANDALONE": "true"}
    }
  }
}

Standalone development needs no server or keys, but it must be explicitly enabled. Production MCP always delegates to an authenticated HTTP authority.

See MCP Client Setup for exact config files, verification commands, remote HTTP setup, and troubleshooting.

Mode 2: Full Stack Server

Got a Raspberry Pi running Pi-hole? A Mac Mini on your desk? An old laptop? That's enough to run the full stack โ€” SearXNG (your own private search engine, disabled by default) plus local JS-rendering content extraction.

server.ts
# Optional: tell Argus it has residential egress to optimize routing
export ARGUS_EGRESS_TYPE=residential
ARGUS_SEARXNG_ENABLED=true docker compose up -d    # SearXNG + Argus
What you haveWhat you get
Any machine with Python 3.11+DuckDuckGo + API providers (no server)
Home server / old laptop (4GB+)Everything โ€” SearXNG, all providers, Crawl4AI, Obscura
Mac Mini M1+ (8GB+)Full stack with headroom
Free cloud VM (1GB)SearXNG + search providers (use residential workers for extraction)

SearXNG takes 512MB of RAM and gives you a private Google-style search engine (disabled by default โ€” set ARGUS_SEARXNG_ENABLED=true) that nobody can rate-limit, block, or charge for. It runs alongside Pi-hole on hardware millions of people already own.

Where Argus Writes Data

Argus code and Argus runtime data are different things.

  • Code lives wherever you install or clone Argus.
  • Runtime corpus data lives in a writable user data directory resolved by platformdirs, or in ARGUS_DATA_ROOT if you override it.

Inspect the exact paths on your machine:

bash
argus paths

By default Argus writes:

  • official docs cache under the resolved docs/cache/
  • research packs under docs/research/
  • workflow run state under workflows/runs/
  • versioned workflow snapshots under snapshots/

This means Argus does not require a sibling ../docs-cache checkout. If you have an older docs-cache tree, import it once with:

bash
argus corpus import-docs-cache -s /path/to/docs-cache

Opinionated Workflows

These workflows build local artifacts, not just transient JSON responses.

Recover A Dead Article

bash
argus recover-article -u "https://example.com/old-post" -t "Example Post"

Argus searches for recovery candidates, extracts the best result, saves the recovered sources locally, and writes a citation-backed report plus manifest.

Capture The Important Parts Of A Site

bash
argus capture-site -u "https://docs.example.com"

Argus stays on-domain, uses sitemap-assisted discovery plus heuristic link scoring, saves the important pages it finds, and writes a detailed summary with references.

Build A Docs + Research Pack

bash
argus build-research-pack -t "example sdk"
argus build-research-pack -t "example sdk" --official-url "https://docs.example.com"

Argus captures official docs into its local docs cache, adds non-official supporting sources from search, and writes a combined research pack with traceable artifacts.

Development

Repo development is pinned to Python 3.12. The package runtime floor is Python 3.11, the production image runs Python 3.12.3, and Python 3.13 is the compatibility CI lane. Required CI passes all three; contributors should use the uv workflow below so local verification matches the canonical lane and does not accidentally use an older system interpreter.

bash
uv sync --python 3.12 --extra dev --extra mcp
uv run pytest tests/ -v --tb=short

The repo includes .python-version with 3.12 so uv, pyenv, and similar tools pick the right interpreter by default. More contributor guidance lives in CONTRIBUTING.md.

Providers

Read the full README โ†’View source on GitHub โ†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks โ€” not a rating.

GitHub stars
5
Stargazers on the source repository.
Last commit
1mo ago
Most recent push to the default branch.
Directory activity
1 views
Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet โ€” be the first to share how this listing worked for you.

Frequently Asked Questions about Argus

Yes, Argus provides zero-key start with DuckDuckGo and Yahoo search providers available immediately after installation.

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Technical Specs & Signals

Category๐Ÿ”ŽSearch & Data Extraction
More technical detailsExpand โ–พ
TransportSTDIO
RuntimePython
Last updatedAug 10, 2026
Views1
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars5
GitHub Star CountTotal stargazers on GitHub representing community popularity (5 stars).
Last commit1mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Aug 10, 2026
40Quality signal: Fair ยท 40/100How this signal is calculated โ–พ
Server availabilityNot measured

Not scored for repo-hosted servers โ€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools16/30
Adoption & activity4/15
Community engagement0/10

A guidance signal from public completeness & health data โ€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 27d ago via OSV.dev ยท argus-search (PyPI)

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