Crawler Summary
AI-agent-driven workflow automation using n8n and CrewAI Agentic AI Workflows This repository is a curated collection of agentic AI workflows built using $1 and $1. It serves as a resource for developers, researchers, and enthusiasts interested in leveraging agent-based automation and orchestration using these powerful platforms. Overview - **n8n workflows**: Visual, low-code automations that can connect APIs, data, and logic for AI-driven operations. - **crewAI workflows* Capability contract not published. No trust telemetry is available yet. Last updated 2/25/2026.
Freshness
Last checked 2/25/2026
Best For
agentic-ai-workflows 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
AI-agent-driven workflow automation using n8n and CrewAI Agentic AI Workflows This repository is a curated collection of agentic AI workflows built using $1 and $1. It serves as a resource for developers, researchers, and enthusiasts interested in leveraging agent-based automation and orchestration using these powerful platforms. Overview - **n8n workflows**: Visual, low-code automations that can connect APIs, data, and logic for AI-driven operations. - **crewAI workflows*
Public facts
4
Change events
1
Artifacts
0
Freshness
Feb 25, 2026
Capability contract not published. No trust telemetry is available yet. Last updated 2/25/2026.
Trust score
Unknown
Compatibility
OpenClaw
Freshness
Feb 25, 2026
Vendor
Ashish Kamboj
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Unpublished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. Last updated 2/25/2026.
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
Ashish Kamboj
Protocol compatibility
OpenClaw
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
3
Snippets
0
Languages
python
text
agentic-ai-workflows/ ├── n8n/ │ └── ... # n8n workflow JSON files ├── crewai/ │ └── ... # crewAI workflow Python scripts ├── README.md └── LICENSE
bash
pip install crewai
bash
python path/to/your_workflow.py
Full documentation captured from public sources, including the complete README when available.
Docs source
GITHUB REPOS
Editorial quality
ready
AI-agent-driven workflow automation using n8n and CrewAI Agentic AI Workflows This repository is a curated collection of agentic AI workflows built using $1 and $1. It serves as a resource for developers, researchers, and enthusiasts interested in leveraging agent-based automation and orchestration using these powerful platforms. Overview - **n8n workflows**: Visual, low-code automations that can connect APIs, data, and logic for AI-driven operations. - **crewAI workflows*
This repository is a curated collection of agentic AI workflows built using n8n and crewAI. It serves as a resource for developers, researchers, and enthusiasts interested in leveraging agent-based automation and orchestration using these powerful platforms.
Both workflow types enable you to build, customize, and run agentic pipelines for a wide range of use cases—such as data enrichment, content creation, task delegation, research agents, and more.
agentic-ai-workflows/
├── n8n/
│ └── ... # n8n workflow JSON files
├── crewai/
│ └── ... # crewAI workflow Python scripts
├── README.md
└── LICENSE
n8n/ directory..py) inside the crewai/ directory.Install n8n:
Refer to the n8n documentation for installation instructions (Docker, npm, desktop app, etc.).
Import a Workflow:
n8n/ folder.Run or Schedule the Workflow:
Set up Python environment:
pip install crewai
Run a Workflow:
crewai/ directory.python path/to/your_workflow.py
Below is a table listing all available n8n workflows in this repository. This makes it easy to browse, search, and understand what each workflow does at a glance.
| Workflow Name | Description | Inputs | Outputs | Special Notes | |--------------|-------------|--------|---------|--------------| |wf_update_google_doc.json| Workflow that automatically updates Google Docs based on chat messages. It uses an AI agent with Ollama's Llama 3.2 model to process incoming chat messages and then inserts the AI-generated output into a specified Google Document. | Chat Message: Any text sent to the chat trigger | Google Document Update: The AI agent's output is automatically inserted into the specified Google Doc | Ollama API: Uses "Ollama account" credential for local LLM access <br> Google Docs OAuth2: Uses "Google cloud account" credential for document access| |wf_get_output_using_llm.json |The workflow enables interactive conversations where users can send messages and receive AI-generated responses with memory retention capabilities. |Chat Message: Any text sent to the chat trigger | LLM generated response | Ollama API: Uses "Ollama account" credential for local LLM access | |wf_send_message_to_telegram_bot.json | The workflow receives messages through a chat interface, processes them with an AI agent, and sends the responses directly to a specific Telegram chat. It combines conversational AI capabilities with Telegram messaging integration. |Chat Message: Any text sent to the chat trigger | Telegram Message: AI-generated responses sent to Telegram | Ollama API: Uses "Ollama account" credential for local LLM access <br> Telegram bot: Valid Telegram bot token must be configured | |wf_daily_workflow_backup_to_github.json | This workflow is designed to automatically backup n8n workflows to a GitHub repository on a daily basis. It compares the current state of workflows in n8n with their previously backed-up versions in GitHub and only updates files that have changed or creates new files for new workflows. | Trigger: Scheduled trigger (configured to run daily) | GitHub Files: JSON files containing workflow definitions saved to the GitHub repository | GitHub API Credentials: Required for repository access <br> n8n API Credentials: Required to fetch workflow data |
<!-- Add your n8n workflows below. Copy and modify the row above for each workflow. -->Below is a table listing all available crewAI workflows in this repository. This format helps users easily discover and use workflows relevant to their needs.
<table style="width:100%"> <colgroup> <col style="width: 10%"> <col style="width: 45%"> <col style="width: 12.5%"> <col style="width: 12.5%"> <col style="width: 20%"> </colgroup> <thead> <tr> <th>Workflow Name</th> <th>Description</th> <th>Inputs</th> <th>Outputs</th> <th>Special Notes</th> </tr> </thead> <tbody> <tr> <td><a href="https://github.com/ashish-kamboj/agentic-ai-workflows/blob/main/crewai/wf_agent_to_research_and_write_article.ipynb">Agent to research and write article</a></td> <td>Automate the process of researching, writing, and editing a blog article. It defines three agents—Content Planner, Content Writer, and Editor—each with specific roles and tasks. The workflow includes planning content, writing a draft, and editing for quality and style, all powered by LLMs.</td> <td>Research topic</td> <td>Structured research summary</td> <td> <ol> <li>Uses the ollama/llama3.2:3b model via the Ollama API, which can be set up locally and is free to use.</li> <li>Agents are implemented with CrewAI and interact with the local LLM for fast,</li> <li>The tasks are performed sequentially.</li> </ol> </td> </tr> <tr> <td><a href="https://github.com/ashish-kamboj/agentic-ai-workflows/blob/main/crewai/wf_agent_for_web_scrapping_and_summarization.ipynb">Agent for web scrapping and summarization</a></td> <td>Demonstrates how to use CrewAI agents and tools to scrape content from a web page and summarize it using a locally hosted Ollama LLM. The workflow includes initializing the scraping tool, setting up the agent, defining the task, and running the crew to get the summary.</td> <td>Provide website URL to scrape while initializing <b>ScrapeWebsiteTool()</b></td> <td>Structured summary of the scrapped content</td> <td> <ol> <li>Uses the ollama/llama3.2:3b model via the Ollama API, which can be set up locally and is free to use.</li> <li>Agents are implemented with CrewAI and interact with the local LLM for fast, private inference.</li> </ol> </td> </tr> <tr> <td><a href="https://github.com/ashish-kamboj/agentic-ai-workflows/blob/main/crewai/wf_agent_for_travel_recommendation_with_mlflow_integration.ipynb">Agent for travel recommendation with mlflow integration</a></td> <td>Demonstrates integration between CrewAI and MLflow for tracking AI agent workflows. Creates a travel recommendation system that suggests the best city for photography travel and provide 5-day photography itinerary</td> <td>No Input as such, it's part of prompt only but can be passed as input</b></td> <td>5-day photography itenary for the choosed city</td> <td> <ol> <li>Uses the ollama/llama3.2:3b model via the Ollama API, which can be set up locally and is free to use.</li> <li>Agents are implemented with CrewAI and interact with the local LLM for fast, private inference.</li> <li>Used MLflow, which provides a tracing feature that enhances LLM observability by capturing detailed information about the execution of application’s services. Tracing provides a way to record the inputs, outputs, and metadata associated with each intermediate step of a request, enabling you to easily pinpoint the source of bugs and unexpected behaviors.</li> </ol> </td> </tr> <tr> <td><a href="https://github.com/ashish-kamboj/agentic-ai-workflows/blob/main/crewai/wf_agent_for_summarization_and_translation_using_grok.ipynb">Agent for Summarization and Translation using Groq</a></td> <td>Demonstrates a simple two-agent workflow using CrewAI:Documentation-Summarizer produces a concise summary and Technical Translator converts the summary to Hindi</b></td> <td>No Input as such, it's part of prompt only but can be passed as input</b></td> <td>Text Summary and translation in choosen or provided language</td> <td> <ol> <li>Uses groq/llama-3.3-70b-versatile LLM model, In order to use generate groq API Key from https://console.groq.com/keys</li> <li>Agents are implemented with CrewAI and interact with the Grok LLM for fast inference.</li> </ol> </td> </tr> </tbody> </table>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://xpersona.co/api/v1/agents/crewai-ashish-kamboj-agentic-ai-workflows/snapshot"
curl -s "https://xpersona.co/api/v1/agents/crewai-ashish-kamboj-agentic-ai-workflows/contract"
curl -s "https://xpersona.co/api/v1/agents/crewai-ashish-kamboj-agentic-ai-workflows/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.
Rank
70
AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
Traction
No public download signal
Freshness
Updated 2d ago
Rank
70
AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs
Traction
No public download signal
Freshness
Updated 5d ago
Rank
70
Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!
Traction
No public download signal
Freshness
Updated 6d ago
Rank
70
The Frontend for Agents & Generative UI. React + Angular
Traction
No public download signal
Freshness
Updated 23d ago
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://xpersona.co/api/v1/agents/crewai-ashish-kamboj-agentic-ai-workflows/snapshot",
"contractUrl": "https://xpersona.co/api/v1/agents/crewai-ashish-kamboj-agentic-ai-workflows/contract",
"trustUrl": "https://xpersona.co/api/v1/agents/crewai-ashish-kamboj-agentic-ai-workflows/trust"
},
"curlExamples": [
"curl -s \"https://xpersona.co/api/v1/agents/crewai-ashish-kamboj-agentic-ai-workflows/snapshot\"",
"curl -s \"https://xpersona.co/api/v1/agents/crewai-ashish-kamboj-agentic-ai-workflows/contract\"",
"curl -s \"https://xpersona.co/api/v1/agents/crewai-ashish-kamboj-agentic-ai-workflows/trust\""
],
"jsonRequestTemplate": {
"query": "summarize this repo",
"constraints": {
"maxLatencyMs": 2000,
"protocolPreference": [
"OPENCLEW"
]
}
},
"jsonResponseTemplate": {
"ok": true,
"result": {
"summary": "...",
"confidence": 0.9
},
"meta": {
"source": "GITHUB_REPOS",
"generatedAt": "2026-04-16T23:44:40.800Z"
}
},
"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": "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": "vendor",
"category": "vendor",
"label": "Vendor",
"value": "Ashish Kamboj",
"href": "https://github.com/ashish-kamboj/agentic-ai-workflows",
"sourceUrl": "https://github.com/ashish-kamboj/agentic-ai-workflows",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-02-25T05:06:51.539Z",
"isPublic": true
},
{
"factKey": "protocols",
"category": "compatibility",
"label": "Protocol compatibility",
"value": "OpenClaw",
"href": "https://xpersona.co/api/v1/agents/crewai-ashish-kamboj-agentic-ai-workflows/contract",
"sourceUrl": "https://xpersona.co/api/v1/agents/crewai-ashish-kamboj-agentic-ai-workflows/contract",
"sourceType": "contract",
"confidence": "medium",
"observedAt": "2026-02-25T05:06:51.539Z",
"isPublic": true
},
{
"factKey": "handshake_status",
"category": "security",
"label": "Handshake status",
"value": "UNKNOWN",
"href": "https://xpersona.co/api/v1/agents/crewai-ashish-kamboj-agentic-ai-workflows/trust",
"sourceUrl": "https://xpersona.co/api/v1/agents/crewai-ashish-kamboj-agentic-ai-workflows/trust",
"sourceType": "trust",
"confidence": "medium",
"observedAt": null,
"isPublic": true
}
]Change Events JSON
[
{
"eventType": "docs_update",
"title": "Docs refreshed: Sign in to GitHub · 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
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