I will n8n openclaw jarvis ai hermes ai multi ai agent obsidian mcp ollama claude code


1 ordine in coda
Informazioni su questo servizio
Stuck running Claude Code, Claude Cowork & a pile of unconnected ai agent tools that don't talk to each other? Manual n8n automation, a CRM nobody updates scattered workflow automation cost you hours every week.
I set up a real multi ai agent system: OpenClaw + Claude Code + Claude Cowork on Anthropic's Fable 5, wired with n8n ai agent workflows, mcp server integration & vibe coding practices, on hardened cloud computing infrastructure, not a fragile demo.
SERVICES I OFFER:
- Claude Code setup & fix
- Claude Cowork rollout
- Claude ai agent config
- OpenClaw setup & fix
- Claude automation
- Claude website & claude webapp builds
- Claude to WordPress
- Claude api/mcp/integration
- Claude skills & claude workflow design
- n8n workflow automation
- Zapier automation
- CRM automation: zoho crm, gohighlevel, hubspot
- Rag ai agent pipeline
- Custom ai agent, conversational ai, ai chatbot
- Langchain, langgraph, crewai
- Notion ai dashboard
- AI Voice agent
- API integration
- Autonomous ai, agentic ai, multi agent system
TOOLS:
- OpenClaw
- Claude Code
- Claude Cowork
- Claude Agent
- CrewAI
- n8n
- Zapier
- Makecom
- HubSpot CRM
- Salesforce
- Zoho CRM
- GoHighLevel
- AWS
- Notion AI
- Vapi AI
- Retell AI
- Docker
- Slack
CONTACT ME TO GET STARTED.
Scopri di più su Ethan Innocent
AI Bot Builder and Automation Expert, n8n, CrewAI, OpenClaw, MakeCom, Zapier
- DaStati Uniti
- Membro damar 2026
- Tempo di risposta medio1 ora
- Ultima consegna1 settimana
Lingue
Italiano, Inglese, Francese, Spagnolo, Tedesco, Portoghese, Norvegese
Il mio portfolio
FAQ
Do you support Claude Code Agent Teams, or only subagents?
Both. Subagents for quick, focused tasks that report back; Agent Teams (currently experimental) when workers need to communicate directly, like a frontend/backend/test split.
How do you handle credentials and permissions inside Claude Cowork?
Cowork only reads/writes folders and connectors you've explicitly approved. I configure permission settings so it shows its plan and waits for approval before anything significant runs.
What's your approach to controlling token spend across agents?
I tier models by task, a stronger model for orchestration, lighter models for repetitive worker tasks, and set hard step/spend caps per agent so a stuck loop can't drain your budget.
How do you scope permissions so autonomous ai agents stay safe?
Every agent gets scoped tool access and spend/step limits up front. Anything with real-world consequences requires human approval before it executes, no agent acts outside its defined boundaries.
How does the Notion AI dashboard fit into the system you build?
It's your visibility layer, a Notion AI dashboard showing what each agent is doing, task status, and outputs, so you're not digging through logs to see what ran.

