AionUi
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Crawler Summary
WebClone is now an official Model Context Protocol (MCP) server, making website cloning available to AI agents like Claude, CrewAI, and any MCP-compatible framework! π WebClone <div align="center"> $1 $1 $1 $1 **An async-first website cloning and rendered capture tool for documentation mirrors, AI knowledge bases, and enterprise RAG pipelines.** $1 β’ $1 β’ $1 β’ $1 β’ $1 β’ $1 </div> --- π― Why WebClone WebClone helps teams turn authorized websites and documentation into reproducible source material for AI systems. It can mirror static pages, render JavaScript pages when needed, and Capability contract not published. No trust telemetry is available yet. 9 GitHub stars reported by the source. Last updated 10/9/2026.
Freshness
Last checked 10/9/2026
Best For
webclone is best for crewai, multi-agent workflows where OpenClaw compatibility matters.
Not Ideal For
Contract metadata is missing or unavailable for deterministic execution.
Evidence Sources Checked
editorial-content, GITHUB REPOS, runtime-metrics, public facts pack
WebClone is now an official Model Context Protocol (MCP) server, making website cloning available to AI agents like Claude, CrewAI, and any MCP-compatible framework! π WebClone <div align="center"> $1 $1 $1 $1 **An async-first website cloning and rendered capture tool for documentation mirrors, AI knowledge bases, and enterprise RAG pipelines.** $1 β’ $1 β’ $1 β’ $1 β’ $1 β’ $1 </div> --- π― Why WebClone WebClone helps teams turn authorized websites and documentation into reproducible source material for AI systems. It can mirror static pages, render JavaScript pages when needed, and
Public facts
5
Change events
1
Artifacts
0
Freshness
Oct 9, 2026
Capability contract not published. No trust telemetry is available yet. 9 GitHub stars reported by the source. Last updated 10/9/2026.
Trust score
Unknown
Compatibility
OpenClaw
Freshness
Oct 9, 2026
Vendor
Ruslanmv
Artifacts
0
Benchmarks
0
Last release
Unpublished
Key links, install path, and a quick operational read before the deeper crawl record.
Summary
Capability contract not published. No trust telemetry is available yet. 9 GitHub stars reported by the source. Last updated 10/9/2026.
Setup snapshot
Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.
Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.
Vendor
Ruslanmv
Protocol compatibility
OpenClaw
Adoption signal
9 GitHub stars
Handshake status
UNKNOWN
Crawlable docs
6 indexed pages on the official domain
Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.
Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.
Extracted files
0
Examples
6
Snippets
0
Languages
python
text
Authorized website or docs portal
β
WebClone polite crawler / rendered browser capture
β
HTML mirror + assets + structured_content.json + render_debug_report.json
β
Chunking, embeddings, vector database, search index, or RAG pipeline
β
Grounded AI assistants, copilots, support bots, and internal chatbotsbash
webclone clone-knowledge-page "https://docs.python.org/3/tutorial/index.html" \ --render-js \ --wait-for "div.body" \ --item-selector "div.section, section" \ --item-text-selector "h1, h2, h3" \ --detail-selector "p, li, pre" \ --output ./output/docs-knowledge-page
text
page.rendered.html # final browser-rendered DOM structured_content.json # generic item/detail/label records for ingestion render_debug_report.json # counts, final URL, auth-likelihood diagnostics
bash
webclone clone "https://docs.python.org/3/" \ --recursive \ --max-depth 2 \ --max-pages 100 \ --workers 1 \ --delay 3000 \ --output ./output/docs-mirror
bash
webclone clone http://127.0.0.1:8000 \ --allow-private-networks \ --max-pages 25 \ --workers 1 \ --delay 3000
bash
curl -LsSf https://astral.sh/uv/install.sh | sh
Full documentation captured from public sources, including the complete README when available.
Docs source
GITHUB REPOS
Editorial quality
ready
WebClone is now an official Model Context Protocol (MCP) server, making website cloning available to AI agents like Claude, CrewAI, and any MCP-compatible framework! π WebClone <div align="center"> $1 $1 $1 $1 **An async-first website cloning and rendered capture tool for documentation mirrors, AI knowledge bases, and enterprise RAG pipelines.** $1 β’ $1 β’ $1 β’ $1 β’ $1 β’ $1 </div> --- π― Why WebClone WebClone helps teams turn authorized websites and documentation into reproducible source material for AI systems. It can mirror static pages, render JavaScript pages when needed, and
An async-first website cloning and rendered capture tool for documentation mirrors, AI knowledge bases, and enterprise RAG pipelines.
AI Knowledge Bases β’ Features β’ Quick Start β’ Usage β’ Docker β’ Contributing
</div>WebClone helps teams turn authorized websites and documentation into reproducible source material for AI systems. It can mirror static pages, render JavaScript pages when needed, and export structured content for downstream chunking, embedding, search, and RAG workflows.
The goal is simple: make it easier for AI assistants and chatbots to answer from trusted documentation instead of guessing.
WebClone is designed for:
WebClone is designed to help AI teams create high-quality, source-grounded knowledge bases from websites they own or are authorized to process.
Authorized website or docs portal
β
WebClone polite crawler / rendered browser capture
β
HTML mirror + assets + structured_content.json + render_debug_report.json
β
Chunking, embeddings, vector database, search index, or RAG pipeline
β
Grounded AI assistants, copilots, support bots, and internal chatbots
Use clone-knowledge-page when a page must be rendered like a browser before extracting structured sections. Pick selectors that actually exist on the target page β the example below uses real Sphinx markup from python.org:
webclone clone-knowledge-page "https://docs.python.org/3/tutorial/index.html" \
--render-js \
--wait-for "div.body" \
--item-selector "div.section, section" \
--item-text-selector "h1, h2, h3" \
--detail-selector "p, li, pre" \
--output ./output/docs-knowledge-page
This writes:
page.rendered.html # final browser-rendered DOM
structured_content.json # generic item/detail/label records for ingestion
render_debug_report.json # counts, final URL, auth-likelihood diagnostics
For a normal documentation site, start with polite limits and expand deliberately:
webclone clone "https://docs.python.org/3/" \
--recursive \
--max-depth 2 \
--max-pages 100 \
--workers 1 \
--delay 3000 \
--output ./output/docs-mirror
Use the generated mirror as the reproducible source of truth for your indexing and embedding jobs.
Retry-After handlingaiohttp and asynciomake testmake docker-buildWebClone is designed for legitimate archiving, classroom labs, and authorized security research. Before crawling a target, confirm that you own the system or have written permission to test it.
Security-oriented defaults now include:
localhost, loopback, link-local, private, and reserved IP targets are blocked to reduce SSRF-style misuse and accidental internal-network crawling.--all-domains.--max-asset-bytes prevents unexpectedly large assets from exhausting disk or memory.For an isolated lab or a private documentation server, opt in deliberately. For example, if you are running a local test site at http://127.0.0.1:8000:
webclone clone http://127.0.0.1:8000 \
--allow-private-networks \
--max-pages 25 \
--workers 1 \
--delay 3000
Install from PyPI (published as webclone v1.0.0):
# Recommended: uv (10-100x faster than pip)
curl -LsSf https://astral.sh/uv/install.sh | sh
uv pip install webclone
# Or with plain pip
pip install webclone
Install from source (gets you the Makefile shortcuts too):
git clone https://github.com/ruslanmv/webclone.git
cd webclone
make install # creates .venv/ and installs the CLI
# The webclone entry point is installed inside .venv/, so either:
source .venv/bin/activate
webclone --version # β WebClone version 1.0.0
# β¦or just call the venv binary directly without activating:
.venv/bin/webclone --version
Note:
make installusesuvand installs into.venv/. Thewebclonecommand is only on yourPATHaftersource .venv/bin/activate(or use.venv/bin/webclonedirectly). The Makefile targets (make run,make test, β¦) already use the venv automatically.
Smoke-test the install:
make run # clones example.com β ./demo_output
.venv/bin/webclone --version # WebClone version 1.0.0
.venv/bin/webclone info https://example.com
# Clone a single page with safe defaults
webclone clone https://example.com
# Crawl a documentation site politely for a RAG source corpus
webclone clone https://docs.python.org/3/ \
--output ./my_mirror \
--recursive \
--max-depth 2 \
--max-pages 100 \
--workers 1 \
--delay 3000
# Render one authorized knowledge page and export structured JSON.
# Use selectors that actually exist on the page you're capturing
# (Sphinx-built Python docs use `div.body`, NOT `.body section`).
webclone clone-knowledge-page https://docs.python.org/3/tutorial/index.html \
--render-js \
--wait-for "div.body" \
--item-selector "div.section, section" \
--item-text-selector "h1, h2, h3" \
--detail-selector "p, li, pre"
That's it! WebClone creates reproducible mirrors and structured capture artifacts you can feed into chunking, embedding, search, and RAG pipelines.
These commands were run on a clean install and the outputs below are the actual results β copy/paste and they will work.
| # | Command | Result |
|---|---------|--------|
| 1 | webclone info https://example.com | Status 200, 528 bytes, 1 link parsed |
| 2 | webclone clone https://example.com --max-pages 1 --no-pdf | 1 page, 0 assets, ~2.3s |
| 3 | webclone clone https://httpbin.org/html --max-pages 1 --no-pdf | 1 page, saved to pages/page_1.html |
| 4 | webclone clone https://docs.python.org/3/library/typing.html --max-pages 1 --no-pdf | 24 files: 5 CSS, 10 JS, 1 image, 7 HTML, 1 other |
| 5 | webclone clone 'https://en.wikipedia.org/wiki/Web_scraping' --recursive --max-depth 1 --max-pages 3 --no-pdf | 3 pages, 23 assets, 1.77 MB, ~9s β recursion + asset downloader both working |
Run the whole verification block in one go:
source .venv/bin/activate
webclone info https://example.com
webclone clone https://example.com -o /tmp/demo_example --max-pages 1 --no-pdf
webclone clone https://httpbin.org/html -o /tmp/demo_httpbin --max-pages 1 --no-pdf
webclone clone https://docs.python.org/3/library/typing.html -o /tmp/demo_pydocs --max-pages 1 --no-pdf
webclone clone 'https://en.wikipedia.org/wiki/Web_scraping' \
-o /tmp/demo_wiki --recursive --max-depth 1 --max-pages 3 --no-pdf
Tip β single-shot authenticated capture: if a saved cookie file in
./cookies/*.jsonmatches the target domain,webclone clone <url>auto-detects it and automatically turns on--render-js. You can just runwebclone clone https://internal.example.com/pageand it Just Works.
WebClone now includes a professional, native desktop interface built with modern Tkinter for superior performance:
# Install with GUI support
make install-gui
# Launch the Enterprise Desktop GUI
make gui

The GUI opens instantly as a native desktop application with:
Perfect for everyone! No command line required - professional desktop interface with instant startup, native performance, and seamless OS integration.
Advantages over web-based GUIs: β Instant startup (no server to launch) β Native desktop performance β Better OS integration (file dialogs, notifications) β No port conflicts β Offline-friendly
WebClone is now an official Model Context Protocol (MCP) server, making website cloning available to AI agents like Claude, CrewAI, and any MCP-compatible framework!
# Install MCP server (adds the `webclone-mcp` entry point to .venv/bin/)
make install-mcp
# Run the server directly to verify it starts (stdio protocol; Ctrl+C to exit)
make mcp
Wire it into Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json on macOS, ~/.config/Claude/claude_desktop_config.json on Linux):
{
"mcpServers": {
"webclone": {
"command": "/absolute/path/to/webclone/.venv/bin/webclone-mcp"
}
}
}
AI agents can now:
Example with Claude:
You: Clone the FastAPI documentation website
Claude: I'll clone that for you.
[Uses WebClone MCP tool]
β
Cloned 127 pages, 543 assets, 45.2 MB total!
Compatible with:
π See: docs/MCP_GUIDE.md and MCP_QUICKSTART.md
WebClone offers four ways to use it:
π¨ Desktop GUI (Easiest - Enterprise Edition)
make gui
π€ MCP Server (For AI Agents)
make install-mcp
π» Command Line (Most Powerful)
webclone clone https://example.com
π Python API (Most Flexible)
from webclone.core import AsyncCrawler
# ... your code
# Show help
webclone --help
# Clone a website
webclone clone <URL> [OPTIONS]
# Analyze a page without downloading
webclone info <URL>
webclone clone https://example.com \
--output ./mirror # Output directory (default: website_mirror)
--recursive # Follow discovered links (default: off)
--workers 1 # Concurrent workers (default: 1)
--max-pages 100 # Maximum pages to crawl (0 = unlimited)
--max-depth 3 # Maximum crawl depth (0 = unlimited)
--delay 3000 # Delay between requests in ms
--no-assets # Skip downloading CSS, JS, images
--no-pdf # Skip PDF generation
--all-domains # Follow links to other domains
--verbose # Detailed logging output
--json-logs # JSON-formatted logs for parsing
For rendered knowledge-page extraction (selectors must match real elements on the target):
webclone clone-knowledge-page https://docs.python.org/3/tutorial/index.html \
--render-js \
--wait-for "div.body" \
--item-selector "div.section, section" \
--item-text-selector "h1, h2, h3" \
--detail-selector "p, li, pre" \
--output ./knowledge-page
# Single page, fast smoke test
webclone clone https://example.com --max-pages 1 --no-pdf
# Crawl Wikipedia article + linked pages (verified: 3 pages, 23 assets, ~9s)
webclone clone 'https://en.wikipedia.org/wiki/Web_scraping' \
--recursive --max-depth 1 --max-pages 3 --no-pdf
# Clone a documentation page with all its CSS/JS/images
# (verified: 24 files for https://docs.python.org/3/library/typing.html)
webclone clone https://docs.python.org/3/library/typing.html --max-pages 1 --no-pdf
# Clone a documentation site recursively for a RAG source corpus
webclone clone https://docs.python.org/3/ \
--recursive --max-depth 3 --max-pages 250 --workers 1 --delay 3000
# Render a JavaScript documentation page before extracting structured content
webclone clone-knowledge-page https://docs.python.org/3/tutorial/index.html \
--render-js \
--wait-for "div.body" \
--item-selector "div.section, section" \
--item-text-selector "h1, h2, h3" \
--detail-selector "p, li, pre"
# Production mode with JSON logs
webclone clone https://example.com --json-logs --output /var/data/mirror
For private documentation that you are authorized to access, save a browser session once and reuse its cookies for later rendered captures.
# Run the interactive authentication examples
python examples/authenticated_crawl.py
Python API for saved sessions:
from pathlib import Path
from webclone.models.config import SeleniumConfig
from webclone.services.selenium_service import SeleniumService
# Open a visible browser and save cookies after manual sign-in.
config = SeleniumConfig(headless=False)
service = SeleniumService(config)
service.start_driver()
service.manual_login_session(
"https://example.com",
Path("./cookies/example.json"),
)
# Later, reuse the cookies for an authorized browser session.
config = SeleniumConfig(headless=True)
service = SeleniumService(config)
service.start_driver()
service.navigate_to("https://example.com")
service.load_cookies(Path("./cookies/example.json"))
See Authentication Guide for detailed instructions.
Run WebClone in a containerized environment:
# Build the image
make docker-build
# Or manually
docker build -t webclone:latest .
# Run a clone
docker run --rm -v $(pwd)/output:/data webclone:latest \
clone https://example.com --max-pages 10
# Interactive shell
docker run --rm -it -v $(pwd)/output:/data \
--entrypoint /bin/bash webclone:latest
version: '3.8'
services:
webclone:
image: webclone:latest
volumes:
- ./output:/data
command: clone https://example.com --max-pages 25 --workers 1 --delay 3000
environment:
- WEBCLONE_MAX_PAGES=100
WebClone follows Clean Architecture principles:
src/webclone/
βββ cli.py # Typer CLI interface
βββ core/ # Core business logic
β βββ crawler.py # Async web crawler
β βββ downloader.py # Asset downloader
β βββ rendered_fetcher.py # Selenium rendered capture
β βββ content_extractor.py # Structured content extraction for RAG
βββ models/ # Pydantic data models
β βββ config.py # Configuration schemas
β βββ metadata.py # Result metadata
βββ services/ # External service integrations
β βββ selenium_service.py
βββ utils/ # Shared utilities
βββ logger.py
βββ helpers.py
asyncio for maximum concurrency# Clone the repository
git clone https://github.com/ruslanmv/webclone.git
cd webclone
# Install with dev dependencies (creates .venv/ with pytest, ruff, mypy, bandit)
make dev
# Run tests β 70 passing
make test
# Format code
make format
# Full test suite with coverage
make test
# β 70 passed in ~3s
# Fast tests without coverage
make test-fast
# Generate HTML coverage report (opens htmlcov/index.html)
make coverage
The Makefile invokes
.venv/bin/pytest/.venv/bin/ruff/ etc. directly, so the targets work whether or not the venv is activated.
# Lint with ruff (the codebase has known lint debt; CI does not block on it)
make lint
# Type check with mypy
make typecheck
# Format code
make format
# Run all quality checks
make audit
We welcome contributions! Please see CONTRIBUTING.md for guidelines.
git checkout -b feature/amazing-feature)make audit)git commit -m 'Add amazing feature')git push origin feature/amazing-feature)Tested on a standard 4-core machine with 100 Mbps connection:
| Website Type | Pages | Assets | Time (WebClone) | Time (wget) | Speedup | |--------------|-------|--------|------------------|-------------|---------| | Static Site | 50 | 200 | 8s | 45s | 5.6x | | Blog | 100 | 500 | 25s | 3m 20s | 8.0x | | Documentation| 200 | 800 | 1m 10s | 12m 15s | 10.5x | | SPA/Dynamic | 30 | 150 | 35s | N/A* | β |
*wget cannot render JavaScript-based SPAs
This project is licensed under the Apache License 2.0 - see the LICENSE file for details.
Ruslan Magana
If you find WebClone useful, please consider giving it a star! β
Made with β€οΈ by Ruslan Magana
</div>Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.
Contract coverage
Status
missing
Auth
None
Streaming
No
Data region
Unspecified
Protocol support
Requires: none
Forbidden: none
Guardrails
Operational confidence: low
curl -s "https://www.xpersona.co/api/v1/agents/crewai-ruslanmv-webclone/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-ruslanmv-webclone/contract"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-ruslanmv-webclone/trust"
Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.
Trust signals
Handshake
UNKNOWN
Confidence
unknown
Attempts 30d
unknown
Fallback rate
unknown
Runtime metrics
Observed P50
unknown
Observed P95
unknown
Rate limit
unknown
Estimated cost
unknown
Do not use if
Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.
Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.
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Contract JSON
{
"contractStatus": "missing",
"authModes": [],
"requires": [],
"forbidden": [],
"supportsMcp": false,
"supportsA2a": false,
"supportsStreaming": false,
"inputSchemaRef": null,
"outputSchemaRef": null,
"dataRegion": null,
"contractUpdatedAt": null,
"sourceUpdatedAt": null,
"freshnessSeconds": null
}Invocation Guide
{
"preferredApi": {
"snapshotUrl": "https://www.xpersona.co/api/v1/agents/crewai-ruslanmv-webclone/snapshot",
"contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-ruslanmv-webclone/contract",
"trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-ruslanmv-webclone/trust"
},
"curlExamples": [
"curl -s \"https://www.xpersona.co/api/v1/agents/crewai-ruslanmv-webclone/snapshot\"",
"curl -s \"https://www.xpersona.co/api/v1/agents/crewai-ruslanmv-webclone/contract\"",
"curl -s \"https://www.xpersona.co/api/v1/agents/crewai-ruslanmv-webclone/trust\""
],
"jsonRequestTemplate": {
"query": "summarize this repo",
"constraints": {
"maxLatencyMs": 2000,
"protocolPreference": [
"OPENCLEW"
]
}
},
"jsonResponseTemplate": {
"ok": true,
"result": {
"summary": "...",
"confidence": 0.9
},
"meta": {
"source": "GITHUB_REPOS",
"generatedAt": "2026-10-10T06:42:07.038Z"
}
},
"retryPolicy": {
"maxAttempts": 3,
"backoffMs": [
500,
1500,
3500
],
"retryableConditions": [
"HTTP_429",
"HTTP_503",
"NETWORK_TIMEOUT"
]
}
}Trust JSON
{
"status": "unavailable",
"handshakeStatus": "UNKNOWN",
"verificationFreshnessHours": null,
"reputationScore": null,
"p95LatencyMs": null,
"successRate30d": null,
"fallbackRate": null,
"attempts30d": null,
"trustUpdatedAt": null,
"trustConfidence": "unknown",
"sourceUpdatedAt": null,
"freshnessSeconds": null
}Capability Matrix
{
"rows": [
{
"key": "OPENCLEW",
"type": "protocol",
"support": "unknown",
"confidenceSource": "profile",
"notes": "Listed on profile"
},
{
"key": "crewai",
"type": "capability",
"support": "supported",
"confidenceSource": "profile",
"notes": "Declared in agent profile metadata"
},
{
"key": "multi-agent",
"type": "capability",
"support": "supported",
"confidenceSource": "profile",
"notes": "Declared in agent profile metadata"
}
],
"flattenedTokens": "protocol:OPENCLEW|unknown|profile capability:crewai|supported|profile capability:multi-agent|supported|profile"
}Facts JSON
[
{
"factKey": "vendor",
"category": "vendor",
"label": "Vendor",
"value": "Ruslanmv",
"href": "https://github.com/ruslanmv/webclone",
"sourceUrl": "https://github.com/ruslanmv/webclone",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-10-09T21:09:26.082Z",
"isPublic": true
},
{
"factKey": "protocols",
"category": "compatibility",
"label": "Protocol compatibility",
"value": "OpenClaw",
"href": "https://www.xpersona.co/api/v1/agents/crewai-ruslanmv-webclone/contract",
"sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-ruslanmv-webclone/contract",
"sourceType": "contract",
"confidence": "medium",
"observedAt": "2026-10-09T21:09:26.082Z",
"isPublic": true
},
{
"factKey": "traction",
"category": "adoption",
"label": "Adoption signal",
"value": "9 GitHub stars",
"href": "https://github.com/ruslanmv/webclone",
"sourceUrl": "https://github.com/ruslanmv/webclone",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-10-09T21:09:26.082Z",
"isPublic": true
},
{
"factKey": "docs_crawl",
"category": "integration",
"label": "Crawlable docs",
"value": "6 indexed pages on the official domain",
"href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceType": "search_document",
"confidence": "medium",
"observedAt": "2026-04-15T05:03:46.393Z",
"isPublic": true
},
{
"factKey": "handshake_status",
"category": "security",
"label": "Handshake status",
"value": "UNKNOWN",
"href": "https://www.xpersona.co/api/v1/agents/crewai-ruslanmv-webclone/trust",
"sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-ruslanmv-webclone/trust",
"sourceType": "trust",
"confidence": "medium",
"observedAt": null,
"isPublic": true
}
]Change Events JSON
[
{
"eventType": "docs_update",
"title": "Docs refreshed: Sign in to GitHub Β· GitHub",
"description": "Fresh crawlable documentation was indexed for the official domain.",
"href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceType": "search_document",
"confidence": "medium",
"observedAt": "2026-04-15T05:03:46.393Z",
"isPublic": true
}
]Sponsored
Ads related to webclone and adjacent AI workflows.