Block 1 - Sticky Note
- Type / Role
- n8n-nodes-base.stickyNote - stickyNote
- Config choices
- Version 1
A secure, scalable enterprise AI orchestration layer built on the Model Context Protocol (MCP). This workflow standardizes tool access across all business systems, enforces permission based data ha...
n8n-nodes-base.stickynote, n8n-nodes-base.webhook, n8n-nodes-base.code, n8n-nodes-base.googlesheets, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatanthropic, n8n-nodes-base.httprequest, n8n-nodes-base.merge
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Oneclick AI Squad.
Original n8n.io sourceA secure, scalable enterprise AI orchestration layer built on the Model Context Protocol (MCP). This workflow standardizes tool access across all business systems, enforces permission-based data handling, applies contextual reasoning via Claude AI, and provides a single governance plane for multi-agent AI deployments.
{
"mcpVersion": "1.1",
"agentId": "sales-agent-prod-007",
"jwtToken": "eyJhbGciOiJIUzI1NiJ9...",
"tenantId": "ORG-ACME-001",
"userId": "[email protected]",
"userRole": "sales_manager",
"toolRequests": [
{ "toolName": "crm.get_pipeline", "parameters": { "region": "APAC" } },
{ "toolName": "erp.get_inventory", "parameters": { "sku": "PROD-001" } }
],
"agentGoal": "Prepare a quarterly sales brief for the APAC team meeting",
"dataClassification": "INTERNAL",
"sessionId": "sess-xyz-001"
}
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This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
| Workflow | Orchestrate enterprise MCP AI tool access with Claude and Google Sheets |
|---|---|
| Complexity | advanced |
| Nodes | 23 |
| Categories | Engineering, AI RAG |
| Author | Oneclick AI Squad |
| Published | 22 Feb 2026 |
Use the JSON export at /data/workflows/13592/13592.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
A secure, scalable enterprise AI orchestration layer built on the Model Context Protocol (MCP). This workflow standardizes tool access across all business systems, enforces permission based data ha...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Engineering, AI RAG use case.