Block 1 - Workflow Overview 0
- Type / Role
- n8n-nodes-base.stickyNote - stickyNote
- Config choices
- Version 1
This workflow is provided as-is. Please review and test before using in production.
οΈ NASA Tool MCP Server Complete MCP server exposing all NASA Tool operations to AI agents. Zero configuration needed all 15 operations pre built. Quick Setup Need help? Want access to more work...
n8n-nodes-base.stickynote, @n8n/n8n-nodes-langchain.mcptrigger, n8n-nodes-base.nasatool
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by David Ashby.
Original n8n.io sourceComplete MCP server exposing all NASA Tool operations to AI agents. Zero configuration needed - all 15 operations pre-built.
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β’ MCP Trigger: Serves as your server endpoint for AI agent requests
β’ Tool Nodes: Pre-configured for every NASA Tool operation
β’ AI Expressions: Automatically populate parameters via $fromAI() placeholders
β’ Native Integration: Uses official n8n NASA Tool tool with full error handling
Every possible NASA Tool operation is included:
β’ Get many asteroid neos
β’ Get an asteroid neo feed
β’ Get an asteroid neo lookup
β’ Get the astronomy picture of the day
β’ Get a DONKI coronal mass ejection
β’ Get a DONKI high speed stream
β’ Get a DONKI interplanetary shock
β’ Get a DONKI magnetopause crossing
β’ Get a DONKI notifications
β’ Get a DONKI radiation belt enhancement
β’ Get a DONKI solar energetic particle
β’ Get a DONKI solar flare
β’ Get a DONKI wsa enlil simulation
β’ Get Earth assets
β’ Get Earth imagery
Parameter Handling: AI agents automatically provide values for: β’ Resource IDs and identifiers β’ Search queries and filters β’ Content and data payloads β’ Configuration options
Response Format: Native NASA Tool API responses with full data structure
Error Handling: Built-in n8n error management and retry logic
Connect this MCP server to any AI agent or workflow:
β’ Claude Desktop: Add MCP server URL to configuration β’ Custom AI Apps: Use MCP URL as tool endpoint β’ Other n8n Workflows: Call MCP tools from any workflow β’ API Integration: Direct HTTP calls to MCP endpoints
β’ Complete Coverage: Every NASA Tool operation available
β’ Zero Setup: No parameter mapping or configuration needed
β’ AI-Ready: Built-in $fromAI() expressions for all parameters
β’ Production Ready: Native n8n error handling and logging
β’ Extensible: Easily modify or add custom logic
> π Free for community use! Ready to deploy in under 2 minutes.
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 | π οΈ NASA tool MCP server πͺ all 15 operations |
|---|---|
| Complexity | advanced |
| Nodes | 21 |
| Categories | Engineering, AI Chatbot |
| Author | David Ashby |
| Published | 22 Jun 2025 |
Use the JSON export at /data/workflows/5118/5118.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.
οΈ NASA Tool MCP Server Complete MCP server exposing all NASA Tool operations to AI agents. Zero configuration needed all 15 operations pre built. Quick Setup Need help? Want access to more work...
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 Chatbot use case.