This workflow follows the Agent → Informationextractor recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"name": "Devstash",
"nodes": [
{
"parameters": {
"jsCode": "// Get the output from the 'Webhook' node.\nconst webhookData = $('Webhook').first().json.body\n\n// Get the output from the 'Information Extractor' node.\nconst llmData = $input.first().json.output\n\n// Start building the final object with required fields from the webhook\nconst finalItem = {\n objectID: webhookData.id,\n content: webhookData.content,\n createdAt: webhookData.createdAt,\n};\n\n// Add fields from the LLM output\nfinalItem.title = llmData.title;\nfinalItem.type = llmData.type;\nfinalItem.language = llmData.language;\n\n// Handle the 'note' field: use webhook's note if it exists, otherwise use LLM's\nfinalItem.note = webhookData.note || llmData.note;\n\n// Handle 'tags': combine userTags from webhook and tags from LLM\nconst userTags = webhookData.userTags || [];\nconst llmTags = llmData.tags || [];\n\n// Use a Set to combine and automatically remove duplicates, then convert back to an array\nconst combinedTags = [...new Set([...userTags, ...llmTags])];\nfinalItem.tags = combinedTags;\n\n// The Code node should return an object with a 'json' property\n// containing the data for the next node.\nreturn {\n output: finalItem,\n};"
},
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
-416,
192
],
"id": "94706792-56ef-41aa-b99c-155b3d363600",
"name": "Code"
},
{
"parameters": {
"multipleMethods": true,
"httpMethod": [
"POST",
"DELETE"
],
"path": "/stash",
"authentication": "headerAuth",
"options": {
"allowedOrigins": "*"
}
},
"type": "n8n-nodes-base.webhook",
"typeVersion": 2,
"position": [
-2304,
560
],
"id": "1c20e393-128c-4a7f-855b-2f51f63e913e",
"name": "Webhook",
"credentials": {
"httpHeaderAuth": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"promptType": "define",
"text": "=Insert the following object into Algolia index `{{$('Workflow Variables').item.json.ALGOLIA_INDEX_NAME || 'stashes'}}`:\n\n{{ JSON.stringify($json.output) }}\n\nIf the index is not present create an index first with name `{{$('Workflow Variables').item.json.ALGOLIA_INDEX_NAME || 'stashes'}}` and then retry the insert operation again.",
"hasOutputParser": true,
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 2.1,
"position": [
-48,
192
],
"id": "8594aa82-07cd-4ad3-882a-e7878b42b22f",
"name": "Insert Agent"
},
{
"parameters": {
"promptType": "define",
"text": "=Task: Remove this document from the Algolia index `{{$('Workflow Variables').item.json.ALGOLIA_INDEX_NAME || 'stashes'}}`. \nObject ID to delete: {{ $('Webhook').item.json.body.objectId }}\n",
"hasOutputParser": true,
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 2.1,
"position": [
-720,
864
],
"id": "30c3fb65-ef24-46e6-81f7-4db39d28e1b0",
"name": "Delete Agent"
},
{
"parameters": {
"sseEndpoint": "=https://your-aloglia-server.onrender.com/sse"
},
"type": "@n8n/n8n-nodes-langchain.mcpClientTool",
"typeVersion": 1,
"position": [
80,
464
],
"id": "c63d160e-82cc-4af5-bd3f-b24c3f997058",
"name": "MCP Client"
},
{
"parameters": {
"schemaType": "manual",
"inputSchema": "{\n\t\"type\": \"object\",\n\t\"properties\": {\n\t\t\"result\": {\n\t\t\t\"type\": \"boolean\",\n\t\t\t\"description\": \"Indicates whether the operation was successful\"\n\t\t}\n\t},\n\t\"required\": [\n\t\t\"result\"\n\t]\n}"
},
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"typeVersion": 1.3,
"position": [
-464,
1088
],
"id": "cddf4230-89a8-4d5d-b121-1279a5f87901",
"name": "Delete Op Result Parser"
},
{
"parameters": {
"schemaType": "manual",
"inputSchema": "{\n\t\"type\": \"object\",\n\t\"properties\": {\n\t\t\"result\": {\n\t\t\t\"type\": \"boolean\",\n\t\t\t\"description\": \"Indicates whether the operation was successful\"\n\t\t},\n \"objectId\": {\n \"type\": \"string\",\n \"description\": \"Id of the inserted document\"\n }\n\t},\n\t\"required\": [\n\t\t\"result\"\n\t]\n}"
},
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"typeVersion": 1.3,
"position": [
192,
368
],
"id": "8e7ce8ea-7654-4a09-97cd-38fed77a012e",
"name": "Insert Op Result Parser"
},
{
"parameters": {
"text": "=Based on the provided JSON data, please perform the following tasks:\n1. Generate a concise, descriptive 'title' for the content.\n2. Classify the 'type' of the content as one of the following: 'code', 'command', 'query', 'config', 'note', or 'other'.\n3. Analyze the 'content' to identify the programming 'language'. If it's different from the language provided in the data, use your corrected version.\n4. Generate a list of relevant 'tags' as a JSON array of strings. Do not use the tags from the 'userTags' field in the input data.\n{{ $('Webhook').item.json.body.note ? \"5. A 'note' is already provided, so return it as is.\" : \"5. A 'note' is not provided. Please generate a brief, one-sentence summary of the content to use as a 'note'.\" }}\nProvide the output as a single, valid JSON object containing only these fields: title, type, language, tags, and note.\n\nInput Data:\n{{ JSON.stringify($('Webhook').item.json.body ) }}",
"schemaType": "manual",
"inputSchema": "{\n\t\"type\": \"object\",\n\t\"properties\": {\n\t\t\"title\": {\n\t\t\t\"type\": \"string\"\n\t\t},\n\t\t\"type\": {\n\t\t\t\"type\": \"string\",\n\t\t\t\"enum\": [\n\t\t\t\t\"code\",\n\t\t\t\t\"command\",\n\t\t\t\t\"query\",\n\t\t\t\t\"config\",\n\t\t\t\t\"snippet\",\n\t\t\t\t\"note\",\n\t\t\t\t\"other\"\n\t\t\t]\n\t\t},\n\t\t\"language\": {\n\t\t\t\"type\": \"string\"\n\t\t},\n\t\t\"tags\": {\n\t\t\t\"type\": \"array\",\n\t\t\t\"items\": {\n\t\t\t\t\"type\": \"string\"\n\t\t\t}\n\t\t},\n\t\t\"note\": {\n\t\t\t\"type\": \"string\"\n\t\t}\n\t}\n}",
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.informationExtractor",
"typeVersion": 1.2,
"position": [
-816,
192
],
"id": "aeeb3986-1138-4fa8-93d1-b0eb54df3e72",
"name": "Information Extractor"
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"id": "e68a15a7-c65c-479f-ab23-3a208c50b6a8",
"leftValue": "={{ $json.output.result }}",
"rightValue": "",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
}
}
],
"combinator": "and"
},
"options": {}
},
"type": "n8n-nodes-base.if",
"typeVersion": 2.2,
"position": [
464,
192
],
"id": "77f8be4c-2837-441d-a07a-684c4f45e6e5",
"name": "If"
},
{
"parameters": {
"errorMessage": "Failed to insert!!"
},
"type": "n8n-nodes-base.stopAndError",
"typeVersion": 1,
"position": [
720,
288
],
"id": "9579a25b-931d-4210-99db-073a0c7d86a0",
"name": "Stop and Error"
},
{
"parameters": {},
"type": "n8n-nodes-base.noOp",
"typeVersion": 1,
"position": [
720,
128
],
"id": "b0ca8de8-0b19-4609-bf2c-324fd84a53b6",
"name": "No Operation, do nothing"
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"id": "e68a15a7-c65c-479f-ab23-3a208c50b6a8",
"leftValue": "={{ $json.output.result }}",
"rightValue": "",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
}
}
],
"combinator": "and"
},
"options": {}
},
"type": "n8n-nodes-base.if",
"typeVersion": 2.2,
"position": [
0,
864
],
"id": "097add21-3012-4baa-a204-11f0de65686c",
"name": "If1"
},
{
"parameters": {},
"type": "n8n-nodes-base.noOp",
"typeVersion": 1,
"position": [
240,
752
],
"id": "8e6e0a9c-c410-424b-8e36-cafb42f13f55",
"name": "No Operation, do nothing1"
},
{
"parameters": {
"errorMessage": "Failed to insert!!"
},
"type": "n8n-nodes-base.stopAndError",
"typeVersion": 1,
"position": [
240,
960
],
"id": "8a7eddc3-dfbf-4904-b00b-8eddb1dadd88",
"name": "Stop and Error1"
},
{
"parameters": {
"model": "google/gemini-2.5-flash",
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatOpenRouter",
"typeVersion": 1,
"position": [
-816,
368
],
"id": "81bd37be-e25e-4817-89f3-c514984158a9",
"name": "OpenRouter Extractor Model",
"credentials": {
"openRouterApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"model": "google/gemini-2.0-flash-001",
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatOpenRouter",
"typeVersion": 1,
"position": [
-48,
368
],
"id": "130e17ec-05ca-4a59-a6a9-4756a00d5d1b",
"name": "OpenRouter Model 1",
"credentials": {
"openRouterApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"model": "google/gemini-2.0-flash-001",
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatOpenRouter",
"typeVersion": 1,
"position": [
-720,
1088
],
"id": "a8702785-c026-4f6a-96f1-2f7c07b7fe3d",
"name": "OpenRouter Model 2",
"credentials": {
"openRouterApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"content": "## Data Processing & Field Extraction\nTakes webhook data and uses LLM to extract structured fields (title, type, language, tags, note) from the content. Code node then combines original webhook data with LLM-provided metadata to create complete structured dataset for processing.",
"height": 544,
"width": 784
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
-976,
48
],
"id": "10d8233e-637e-4b27-a5ec-26099124a82f",
"name": "Sticky Note"
},
{
"parameters": {
"content": "## Algolia Data Insertion\nTakes structured metadata from Workflow 1 and uses AI agent to call Algolia MCP server for index insertion. Returns true/false based on operation success - completes workflow on success or throws error on failure.",
"height": 544,
"width": 1040
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
-96,
48
],
"id": "90419312-29e5-414a-847f-0da2e2906d1f",
"name": "Sticky Note1"
},
{
"parameters": {
"content": "## Algolia Data Deletion\nHandles DELETE webhook requests by extracting object ID and passing it to AI agent. Agent calls Algolia MCP server to delete the specified object from the index.",
"height": 608,
"width": 1920
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
-976,
656
],
"id": "d9266b0f-a13a-43e2-9b88-96b126e38ea8",
"name": "Sticky Note2"
},
{
"parameters": {
"sseEndpoint": "https://your-aloglia-server.onrender.com/sse"
},
"type": "@n8n/n8n-nodes-langchain.mcpClientTool",
"typeVersion": 1,
"position": [
-592,
1088
],
"id": "e004097b-2cbe-4519-94de-8397f3f34c2f",
"name": "MCP Client1"
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "a52dadab-5394-4a9d-a6dc-1da4d3a4dd23",
"name": "ALGOLIA_INDEX_NAME",
"value": "",
"type": "string"
},
{
"id": "496617e6-c383-4c14-b121-71c0c1826031",
"name": "=HTTP_METHOD",
"value": "={{ $prevNode.outputIndex === 0 ? \"POST\" : ($prevNode.outputIndex === 1 ? \"DELETE\" : \"\") }}",
"type": "string"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
-1824,
560
],
"id": "2d3e3555-4b2a-4ad6-bf10-829678d22b19",
"name": "Workflow Variables"
},
{
"parameters": {
"content": "## Workflow Variables \nUse this node to define variables that can be accessed throughout the workflow.\nSince global variables are only available on paid plans, this provides a way to simulate global values within a single workflow.",
"height": 592,
"width": 432,
"color": 3
},
"type": "n8n-nodes-base.stickyNote",
"position": [
-1984,
288
],
"typeVersion": 1,
"id": "706e5479-d85d-4a33-a9e0-c746b063d099",
"name": "Sticky Note3"
},
{
"parameters": {
"content": "## Entry Point\nMarks the initial trigger for the workflow. All logic flows from this node.",
"height": 592,
"width": 432,
"color": 4
},
"type": "n8n-nodes-base.stickyNote",
"position": [
-2448,
288
],
"typeVersion": 1,
"id": "3f6c72fc-54a3-4873-abb3-36b0a92bf1f3",
"name": "Sticky Note4"
},
{
"parameters": {
"rules": {
"values": [
{
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"leftValue": "={{ $json.HTTP_METHOD }}",
"rightValue": "POST",
"operator": {
"type": "string",
"operation": "equals"
},
"id": "26421109-3d52-49c7-bc4c-cac1531cb1cb"
}
],
"combinator": "and"
},
"renameOutput": true,
"outputKey": "POST"
},
{
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"id": "bc8602a7-b69d-4403-b711-dc8aa8a44b7c",
"leftValue": "={{ $json.HTTP_METHOD }}",
"rightValue": "DELETE",
"operator": {
"type": "string",
"operation": "equals",
"name": "filter.operator.equals"
}
}
],
"combinator": "and"
},
"renameOutput": true,
"outputKey": "DELETE"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.switch",
"typeVersion": 3.2,
"position": [
-1344,
560
],
"id": "e3fccd56-bd76-4e79-b724-e69b0c4b7615",
"name": "Switch"
},
{
"parameters": {
"content": "## Workflow Router \nThis switch node routes the execution to the appropriate node based on the HTTP method received from the webhook.\n",
"height": 592,
"width": 464
},
"type": "n8n-nodes-base.stickyNote",
"position": [
-1520,
288
],
"typeVersion": 1,
"id": "80d3214b-f82c-49e0-97a0-a3bd7aa5e26a",
"name": "Sticky Note6"
}
],
"connections": {
"Code": {
"main": [
[
{
"node": "Insert Agent",
"type": "main",
"index": 0
}
]
]
},
"Webhook": {
"main": [
[
{
"node": "Workflow Variables",
"type": "main",
"index": 0
}
],
[
{
"node": "Workflow Variables",
"type": "main",
"index": 0
}
]
]
},
"Insert Agent": {
"main": [
[
{
"node": "If",
"type": "main",
"index": 0
}
]
]
},
"MCP Client": {
"ai_tool": [
[
{
"node": "Insert Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Delete Op Result Parser": {
"ai_outputParser": [
[
{
"node": "Delete Agent",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Insert Op Result Parser": {
"ai_outputParser": [
[
{
"node": "Insert Agent",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Information Extractor": {
"main": [
[
{
"node": "Code",
"type": "main",
"index": 0
}
]
]
},
"If": {
"main": [
[
{
"node": "No Operation, do nothing",
"type": "main",
"index": 0
}
],
[
{
"node": "Stop and Error",
"type": "main",
"index": 0
}
]
]
},
"If1": {
"main": [
[
{
"node": "No Operation, do nothing1",
"type": "main",
"index": 0
}
],
[
{
"node": "Stop and Error1",
"type": "main",
"index": 0
}
]
]
},
"Delete Agent": {
"main": [
[
{
"node": "If1",
"type": "main",
"index": 0
}
]
]
},
"OpenRouter Extractor Model": {
"ai_languageModel": [
[
{
"node": "Information Extractor",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"OpenRouter Model 1": {
"ai_languageModel": [
[
{
"node": "Insert Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"OpenRouter Model 2": {
"ai_languageModel": [
[
{
"node": "Delete Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"MCP Client1": {
"ai_tool": [
[
{
"node": "Delete Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Workflow Variables": {
"main": [
[
{
"node": "Switch",
"type": "main",
"index": 0
}
]
]
},
"Switch": {
"main": [
[
{
"node": "Information Extractor",
"type": "main",
"index": 0
}
],
[
{
"node": "Delete Agent",
"type": "main",
"index": 0
}
]
]
}
},
"active": false,
"settings": {
"executionOrder": "v1",
"timezone": "Asia/Kolkata",
"callerPolicy": "workflowsFromSameOwner"
},
"versionId": "d4941b63-789d-4a7f-a507-0c3b5865d646",
"meta": {
"templateCredsSetupCompleted": true
},
"id": "YeyjjpXDBOKIWqxa",
"tags": []
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
httpHeaderAuthopenRouterApi
Pro
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About this workflow
Devstash. Uses agent, mcpClientTool, outputParserStructured, informationExtractor. Webhook trigger; 26 nodes.
Source: https://github.com/bugcacher/devstash/blob/c6601173d2fba75d438c7f68ab50f3e8e6c8e3c3/n8n/devstash-template.json — original creator credit. Request a take-down →
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