{ "id": "mrecjHsKCTsQ6QYC", "meta": { "templateCredsSetupCompleted": true }, "name": "6 Monitor Competitor Social Media Engagement:", "tags": [], "nodes": [ { "id": "5eed5537-b38c-4a15-965b-6aa0433c6409", "name": "\ud83d\udd18 Trigger: Manual Start", "type": "n8n-nodes-base.manualTrigger", "position": [ 180, 0 ], "parameters": {}, "typeVersion": 1 }, { "id": "c45a95e6-3a8f-4198-9b29-ee9a36059ac4", "name": "\ud83d\udd17 Set LinkedIn Company URL", "type": "n8n-nodes-base.set", "position": [ 400, 0 ], "parameters": { "options": {}, "assignments": { "assignments": [ { "id": "01b30c4d-3a89-418a-b939-ac1e886002a4", "name": "URL", "type": "string", "value": "https://www.linkedin.com/company/hubspot/" } ] } }, "typeVersion": 3.4 }, { "id": "c7b82e78-1ef2-4c5f-aff2-a03e3a7ea4b6", "name": "\ud83e\udd16 Agent: Fetch LinkedIn Posts (via MCP Tool)", "type": "@n8n/n8n-nodes-langchain.agent", "position": [ 660, 0 ], "parameters": { "text": "=Scrape the below user profile on LinkedIn and get the latest 5 post data:\n{{ $json.URL }}", "options": {}, "promptType": "define", "hasOutputParser": true }, "typeVersion": 2 }, { "id": "4a43225a-b400-47cf-b252-36516d382ff1", "name": "\ud83c\udf10 Bright Data MCP Client", "type": "n8n-nodes-mcp.mcpClientTool", "position": [ 820, 300 ], "parameters": { "toolName": "web_data_linkedin_company_profile", "operation": "executeTool", "toolParameters": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('Tool_Parameters', ``, 'json') }}" }, "credentials": { "mcpClientApi": { "name": "" } }, "typeVersion": 1 }, { "id": "21324291-7117-44d4-aaff-601d80b93580", "name": "\ud83d\udcc8 Analyze Engagement Metrics", "type": "n8n-nodes-base.code", "position": [ 1160, 0 ], "parameters": { "jsCode": "// Get the posts array from Agent output\nconst posts = $json.output;\n\n// Initialize counters\nlet totalLikes = 0;\nlet totalComments = 0;\n\n// Loop through posts and sum likes and comments\nfor (const post of posts) {\n totalLikes += post.likes;\n totalComments += post.comments;\n}\n\n// Calculate averages\nconst averageLikes = totalLikes / posts.length;\nconst averageComments = totalComments / posts.length;\n\n// Return summary object\nreturn [\n {\n json: {\n totalPosts: posts.length,\n totalLikes: totalLikes,\n totalComments: totalComments,\n averageLikes: averageLikes,\n averageComments: averageComments\n }\n }\n];\n" }, "typeVersion": 2 }, { "id": "469f5efc-276c-449b-ab50-4cd3454946f6", "name": "\ud83d\udce5 Save Averages to Google Sheets", "type": "n8n-nodes-base.googleSheets", "position": [ 1380, 0 ], "parameters": { "columns": { "value": { "Total likes": "={{ $json.totalLikes }}", "Total posts": "={{ $json.totalPosts }}", "Average likes": "={{ $json.averageLikes }}", "Total comments": "={{ $json.totalComments }}", "Average comments": "={{ $json.averageComments }}" }, "schema": [ { "id": "Total posts", "type": "string", "display": true, "required": false, "displayName": "Total posts", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Total likes", "type": "string", "display": true, "required": false, "displayName": "Total likes", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Total comments", "type": "string", "display": true, "required": false, "displayName": "Total comments", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Average likes", "type": "string", "display": true, "required": false, "displayName": "Average likes", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Average comments", "type": "string", "display": true, "required": false, "displayName": "Average comments", "defaultMatch": false, "canBeUsedToMatch": true } ], "mappingMode": "defineBelow", "matchingColumns": [], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {}, "operation": "append", "sheetName": { "__rl": true, "mode": "list", "value": "gid=0", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1FzzslRBkdEgz14zuyy1J5IAMAHgkmdmiYiEqYG9AnOI/edit#gid=0", "cachedResultName": "Sheet1" }, "documentId": { "__rl": true, "mode": "list", "value": "1FzzslRBkdEgz14zuyy1J5IAMAHgkmdmiYiEqYG9AnOI", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1FzzslRBkdEgz14zuyy1J5IAMAHgkmdmiYiEqYG9AnOI/edit?usp=drivesdk", "cachedResultName": "Competitor post analysis average" } }, "credentials": { "googleSheetsOAuth2Api": { "name": "" } }, "typeVersion": 4.6 }, { "id": "8f554af6-1d6d-4225-9ffb-5814e4ca2773", "name": "\ud83e\uddfe Format Post Content", "type": "n8n-nodes-base.code", "position": [ 1640, 0 ], "parameters": { "jsCode": "// Get the Agent output (array of posts)\nconst posts = $('\ud83e\udd16 Agent: Fetch LinkedIn Posts (via MCP Tool)').first().json.output;\n\n// Map each post to its own item\nreturn posts.map(post => {\n return {\n json: post\n };\n});\n" }, "typeVersion": 2 }, { "id": "8274a619-f1d2-4e14-9753-665f060611c1", "name": "\ud83d\udce5 Save Posts to Google Sheets", "type": "n8n-nodes-base.googleSheets", "position": [ 1860, 0 ], "parameters": { "columns": { "value": { "date": "={{ $json.date }}", "likes": "={{ $json.likes }}", "video": "={{ $json.videos }}", "content": "={{ $json.content }}", "comments": "={{ $json.comments }}", "post link": "={{ $json.post_link }}", "Competitor": "={{ $json.competitor }}", "Post title": "={{ $json.post_title }}" }, "schema": [ { "id": "Competitor", "type": "string", "display": true, "required": false, "displayName": "Competitor", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Post title", "type": "string", "display": true, "required": false, "displayName": "Post title", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "date", "type": "string", "display": true, "required": false, "displayName": "date", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "likes", "type": "string", "display": true, "required": false, "displayName": "likes", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "comments", "type": "string", "display": true, "required": false, "displayName": "comments", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "content", "type": "string", "display": true, "required": false, "displayName": "content", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "post link", "type": "string", "display": true, "required": false, "displayName": "post link", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "video", "type": "string", "display": true, "required": false, "displayName": "video", "defaultMatch": false, "canBeUsedToMatch": true } ], "mappingMode": "defineBelow", "matchingColumns": [], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {}, "operation": "append", "sheetName": { "__rl": true, "mode": "list", "value": "gid=0", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1R-rAkvVh1lhbPrFsxuBUXNMFFFgsyIWzS4OritRiHLU/edit#gid=0", "cachedResultName": "Sheet1" }, "documentId": { "__rl": true, "mode": "list", "value": "1R-rAkvVh1lhbPrFsxuBUXNMFFFgsyIWzS4OritRiHLU", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1R-rAkvVh1lhbPrFsxuBUXNMFFFgsyIWzS4OritRiHLU/edit?usp=drivesdk", "cachedResultName": "Competitor post analysis" } }, "credentials": { "googleSheetsOAuth2Api": { "name": "" } }, "typeVersion": 4.6 }, { "id": "da8ebb55-18c8-4f17-882d-6ddee3f17533", "name": "Sticky Note", "type": "n8n-nodes-base.stickyNote", "position": [ 140, -720 ], "parameters": { "color": 3, "width": 420, "height": 900, "content": "### \ud83d\udd39 **SECTION 1: Start & Input**\n\n#### \ud83e\udde9 Nodes:\n\n* `\ud83d\udd18 Trigger: Manual Start`\n* `\ud83d\udd17 Set LinkedIn Company URL`\n\n#### \ud83d\udca1 What Happens:\n\nThis section is your starting point. You **manually execute** the workflow by clicking the **play button**, and then you **enter the LinkedIn company profile URL** in a form field.\n\n#### \u2705 Beginner Tip:\n\nYou don\u2019t need coding skills. Just copy the company\u2019s LinkedIn URL (e.g., `https://www.linkedin.com/company/openai`) and paste it here. This kicks off the whole automation!\n\n---\n\n" }, "typeVersion": 1 }, { "id": "df570435-b29c-444f-99a0-f3d8bf951673", "name": "OpenAI Chat Model", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "position": [ 600, 300 ], "parameters": { "model": { "__rl": true, "mode": "list", "value": "gpt-4o-mini" }, "options": {} }, "credentials": { "openAiApi": { "name": "" } }, "typeVersion": 1.2 }, { "id": "54b4118c-47d6-4aa4-9f73-d3d2389a7107", "name": "Sticky Note1", "type": "n8n-nodes-base.stickyNote", "position": [ 600, -860 ], "parameters": { "color": 5, "width": 420, "height": 1040, "content": "### \ud83e\udd16 **SECTION 2: Smart Scraper Agent**\n\n#### \ud83e\udde9 Node:\n\n* `\ud83e\udd16 Agent: Fetch LinkedIn Posts (via MCP Tool)`\n\n##### \ud83e\udde0 Sub-Nodes Inside the Agent:\n\n* `\ud83e\udde0 Chat Model`: Understands your scraping request in natural language.\n* `\ud83c\udf10 Bright Data MCP Client`: Actually visits LinkedIn via mobile proxies and scrapes the data.\n* `\ud83e\uddfe Parse AI Response`: Converts raw results into structured post data.\n\n#### \ud83d\udca1 What Happens:\n\nThis smart AI agent (powered by OpenAI + Bright Data) goes to the LinkedIn company page, **scrapes the latest 5 posts**, and organizes them. Bright Data MCP lets it **bypass anti-bot systems** by using mobile IPs, so it's reliable even on protected sites like LinkedIn.\n\n#### \u2705 Beginner Tip:\n\nYou don\u2019t write any scraping code! The AI understands what to do and fetches posts like a human browser would. This is **completely no-code** for you.\n\n---\n\n" }, "typeVersion": 1 }, { "id": "4fe62240-87e5-45ae-991e-a0ca07500c93", "name": "Sticky Note2", "type": "n8n-nodes-base.stickyNote", "position": [ 1100, -680 ], "parameters": { "color": 6, "width": 420, "height": 860, "content": "### \ud83d\udcca **SECTION 3: Analyze & Save Metrics**\n\n#### \ud83e\udde9 Nodes:\n\n* `\ud83d\udcc8 Analyze Engagement Metrics`\n* `\ud83d\udce5 Save Averages to Google Sheets`\n\n#### \ud83d\udca1 What Happens:\n\nHere, the automation **calculates the average** values (like likes, comments, etc.) from the 5 scraped posts using simple JavaScript logic.\n\nThen, it **saves these average values into your first Google Sheet** so you can track performance over time.\n\n#### \u2705 Beginner Tip:\n\nThis helps you **measure content engagement** across different companies. You can reuse this for competitive research, content benchmarking, or client reporting.\n\n---\n\n" }, "typeVersion": 1 }, { "id": "a2897619-9086-4a99-8fa6-551fffc8893f", "name": "Sticky Note3", "type": "n8n-nodes-base.stickyNote", "position": [ 1580, -640 ], "parameters": { "color": 2, "width": 420, "height": 820, "content": "### \ud83d\udcc4 **SECTION 4: Format & Store Full Posts**\n\n#### \ud83e\udde9 Nodes:\n\n* `\ud83e\uddfe Format Post Content`\n* `\ud83d\udce5 Save Posts to Google Sheets`\n\n#### \ud83d\udca1 What Happens:\n\nNow that averages are stored, this section **formats the full content of the 5 posts** (text, date, likes, etc.) for better readability and structure.\n\nThen, it **stores each individual post into a second Google Sheet** for deeper post-level insights.\n\n#### \u2705 Beginner Tip:\n\nThis gives you a historical view of what each company is posting\u2014great for content strategy or trend analysis.\n\n---\n\n" }, "typeVersion": 1 }, { "id": "55dbafa4-8ad9-4a4d-b5bb-2b42facb55e4", "name": "Sticky Note9", "type": "n8n-nodes-base.stickyNote", "position": [ -1660, -700 ], "parameters": { "color": 4, "width": 1300, "height": 320, "content": "=======================================\n WORKFLOW ASSISTANCE\n=======================================\nFor any questions or support, please contact:\n Yaron@nofluff.online\n\nExplore more tips and tutorials here:\n - YouTube: https://www.youtube.com/@YaronBeen/videos\n - LinkedIn: https://www.linkedin.com/in/yaronbeen/\n=======================================\n" }, "typeVersion": 1 }, { "id": "d222b12b-dfed-4240-9580-027370214ae0", "name": "Sticky Note4", "type": "n8n-nodes-base.stickyNote", "position": [ -1660, -360 ], "parameters": { "color": 4, "width": 1289, "height": 2578, "content": "## \ud83d\ude80 **LinkedIn Company Post Analyzer Workflow**\n\nThis automation lets you input a LinkedIn company URL, scrape its **latest 5 posts** using **Bright Data MCP**, calculate **engagement averages**, and store everything neatly in **Google Sheets**. Whether you're a digital marketer, analyst, or business owner\u2014this saves time and effort!\n\n---\n\n### \ud83d\udd39 **SECTION 1: Start & Input**\n\n#### \ud83e\udde9 Nodes:\n\n* `\ud83d\udd18 Trigger: Manual Start`\n* `\ud83d\udd17 Set LinkedIn Company URL`\n\n#### \ud83d\udca1 What Happens:\n\nThis section is your starting point. You **manually execute** the workflow by clicking the **play button**, and then you **enter the LinkedIn company profile URL** in a form field.\n\n#### \u2705 Beginner Tip:\n\nYou don\u2019t need coding skills. Just copy the company\u2019s LinkedIn URL (e.g., `https://www.linkedin.com/company/openai`) and paste it here. This kicks off the whole automation!\n\n---\n\n### \ud83e\udd16 **SECTION 2: Smart Scraper Agent**\n\n#### \ud83e\udde9 Node:\n\n* `\ud83e\udd16 Agent: Fetch LinkedIn Posts (via MCP Tool)`\n\n##### \ud83e\udde0 Sub-Nodes Inside the Agent:\n\n* `\ud83e\udde0 Chat Model`: Understands your scraping request in natural language.\n* `\ud83c\udf10 Bright Data MCP Client`: Actually visits LinkedIn via mobile proxies and scrapes the data.\n* `\ud83e\uddfe Parse AI Response`: Converts raw results into structured post data.\n\n#### \ud83d\udca1 What Happens:\n\nThis smart AI agent (powered by OpenAI + Bright Data) goes to the LinkedIn company page, **scrapes the latest 5 posts**, and organizes them. Bright Data MCP lets it **bypass anti-bot systems** by using mobile IPs, so it's reliable even on protected sites like LinkedIn.\n\n#### \u2705 Beginner Tip:\n\nYou don\u2019t write any scraping code! The AI understands what to do and fetches posts like a human browser would. This is **completely no-code** for you.\n\n---\n\n### \ud83d\udcca **SECTION 3: Analyze & Save Metrics**\n\n#### \ud83e\udde9 Nodes:\n\n* `\ud83d\udcc8 Analyze Engagement Metrics`\n* `\ud83d\udce5 Save Averages to Google Sheets`\n\n#### \ud83d\udca1 What Happens:\n\nHere, the automation **calculates the average** values (like likes, comments, etc.) from the 5 scraped posts using simple JavaScript logic.\n\nThen, it **saves these average values into your first Google Sheet** so you can track performance over time.\n\n#### \u2705 Beginner Tip:\n\nThis helps you **measure content engagement** across different companies. You can reuse this for competitive research, content benchmarking, or client reporting.\n\n---\n\n### \ud83d\udcc4 **SECTION 4: Format & Store Full Posts**\n\n#### \ud83e\udde9 Nodes:\n\n* `\ud83e\uddfe Format Post Content`\n* `\ud83d\udce5 Save Posts to Google Sheets`\n\n#### \ud83d\udca1 What Happens:\n\nNow that averages are stored, this section **formats the full content of the 5 posts** (text, date, likes, etc.) for better readability and structure.\n\nThen, it **stores each individual post into a second Google Sheet** for deeper post-level insights.\n\n#### \u2705 Beginner Tip:\n\nThis gives you a historical view of what each company is posting\u2014great for content strategy or trend analysis.\n\n---\n\n## \u2705 Summary: How You Can Use This\n\n| Use Case | How It Helps You |\n| ---------------------------- | ----------------------------------------------------- |\n| \ud83d\udd0d Competitive Monitoring | See what your rivals are posting and how it performs. |\n| \ud83d\udcc8 Marketing Analytics | Track brand performance via LinkedIn posts. |\n| \ud83d\udcca Client Reports | Automate monthly reports on LinkedIn presence. |\n| \ud83d\udca1 Content Strategy Planning | Analyze what kind of posts get the most engagement. |\n\n---\n\n" }, "typeVersion": 1 }, { "id": "e99f86d4-73cc-4bcb-a8d7-24f640abf7d6", "name": "Sticky Note5", "type": "n8n-nodes-base.stickyNote", "position": [ 2080, -640 ], "parameters": { "color": 7, "width": 380, "height": 240, "content": "## I\u2019ll receive a tiny commission if you join Bright Data through this link\u2014thanks for fueling more free content!\n\n### https://get.brightdata.com/1tndi4600b25" }, "typeVersion": 1 }, { "id": "3991b4a5-b3d8-4869-b620-b0eff43e56b1", "name": "Auto-fixing Output Parser", "type": "@n8n/n8n-nodes-langchain.outputParserAutofixing", "position": [ 980, 300 ], "parameters": { "options": {} }, "typeVersion": 1 }, { "id": "c9cfdde4-39e7-42de-a66c-94a1264d7b33", "name": "OpenAI Chat Model1", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "position": [ 940, 560 ], "parameters": { "model": { "__rl": true, "mode": "list", "value": "gpt-4o-mini" }, "options": {} }, "credentials": { "openAiApi": { "name": "" } }, "typeVersion": 1.2 }, { "id": "2e74bb7f-634f-4840-919d-e825feb66b11", "name": "Structured Output Parser", "type": "@n8n/n8n-nodes-langchain.outputParserStructured", "position": [ 1120, 560 ], "parameters": { "jsonSchemaExample": "[\n {\n \"competitor\": \"HubSpot\",\n \"post_title\": \"HubSpot\",\n \"date\": \"3 weeks ago\",\n \"likes\": 54,\n \"comments\": 3,\n \"content\": \"\ud83d\udea8 Nicht weiter scrollen! \ud83d\udea8 Wir sind das \u2728erste\u2728 CRM mit einem Deep-Research-Connector f\u00fcr ChatGPT Deine HubSpot-Daten + das Hirn von ChatGPT = \ud83e\udd2f \ud83d\udd17 Hol dir jetzt den Early Access\",\n \"post_link\": \"https://de.linkedin.com/posts/hubspot_hubspot-und-chatgptpdf-activity-7336304617892306944-Ob8h\",\n \"videos\": []\n },\n {\n \"competitor\": \"HubSpot\",\n \"post_title\": \"HubSpot\",\n \"date\": \"1 day ago\",\n \"likes\": 79,\n \"comments\": 10,\n \"content\": \"when you need a social content framework that's effective AND memorable\",\n \"post_link\": null,\n \"videos\": [\n \"https://dms.licdn.com/playlist/vid/v2/D4D10AQEmIrq4MYknpQ/mp4-640p-30fp-crf28/B4DZetK.GFGkA4-/0/1750957032138?e=2147483647&v=beta&t=PtE4WAUXBXb2VkZChI7m-R4BGONJY0vY0IGCHyX4lXQ\"\n ]\n },\n {\n \"competitor\": \"HubSpot\",\n \"post_title\": \"HubSpot\",\n \"date\": \"4 days ago\",\n \"likes\": 116,\n \"comments\": 12,\n \"content\": \"plot twist: the co-worker who complained about being cold all winter is now the office hero for knowing where the thermostat is\",\n \"post_link\": \"https://www.linkedin.com/posts/hubspot_plot-twist-the-co-worker-who-complained-activity-7343+1234567890-OIh3\",\n \"videos\": []\n },\n {\n \"competitor\": \"HubSpot\",\n \"post_title\": \"HubSpot\",\n \"date\": \"1 week ago\",\n \"likes\": 112,\n \"comments\": 4,\n \"content\": \"meet my new work bestie: Breeze Customer Agent\",\n \"post_link\": null,\n \"videos\": [\n \"https://dms.licdn.com/playlist/vid/v2/D4D10AQGcS77ueYgGeQ/mp4-720p-30fp-crf28/B4DZeITpeIGgBM-/0/1750338545668?e=2147483647&v=beta&t=NrehXjQVj_uk7nHVFrvs18p4-tLUleLObMGKrmsCoqY\"\n ]\n },\n {\n \"competitor\": \"HubSpot\",\n \"post_title\": \"HubSpot\",\n \"date\": \"1 week ago\",\n \"likes\": 104,\n \"comments\": 11,\n \"content\": \"must have been the wind\",\n \"post_link\": null,\n \"videos\": [\n \"https://dms.licdn.com/playlist/vid/v2/D4D05AQG6kJ8EqkBmAw/mp4-640p-30fp-crf28/B4DZeEjsVIGUBg-/0/1750275644735?e=2147483647&v=beta&t=7Pfujdbu6rXW34zKPoDHXrnHG93T900bKVQBFBllbLA\"\n ]\n }\n]\n" }, "typeVersion": 1.2 } ], "active": false, "settings": { "executionOrder": "v1" }, "versionId": "a97cbb59-0a34-41a1-9649-3ef22f0f3b7d", "connections": { "OpenAI Chat Model": { "ai_languageModel": [ [ { "node": "\ud83e\udd16 Agent: Fetch LinkedIn Posts (via MCP Tool)", "type": "ai_languageModel", "index": 0 } ] ] }, "OpenAI Chat Model1": { "ai_languageModel": [ [ { "node": "Auto-fixing Output Parser", "type": "ai_languageModel", "index": 0 } ] ] }, "Structured Output Parser": { "ai_outputParser": [ [ { "node": "Auto-fixing Output Parser", "type": "ai_outputParser", "index": 0 } ] ] }, "\ud83e\uddfe Format Post Content": { "main": [ [ { "node": "\ud83d\udce5 Save Posts to Google Sheets", "type": "main", "index": 0 } ] ] }, "Auto-fixing Output Parser": { "ai_outputParser": [ [ { "node": "\ud83e\udd16 Agent: Fetch LinkedIn Posts (via MCP Tool)", "type": "ai_outputParser", "index": 0 } ] ] }, "\ud83d\udd18 Trigger: Manual Start": { "main": [ [ { "node": "\ud83d\udd17 Set LinkedIn Company URL", "type": "main", "index": 0 } ] ] }, "\ud83c\udf10 Bright Data MCP Client": { "ai_tool": [ [ { "node": "\ud83e\udd16 Agent: Fetch LinkedIn Posts (via MCP Tool)", "type": "ai_tool", "index": 0 } ] ] }, "\ud83d\udd17 Set LinkedIn Company URL": { "main": [ [ { "node": "\ud83e\udd16 Agent: Fetch LinkedIn Posts (via MCP Tool)", "type": "main", "index": 0 } ] ] }, "\ud83d\udcc8 Analyze Engagement Metrics": { "main": [ [ { "node": "\ud83d\udce5 Save Averages to Google Sheets", "type": "main", "index": 0 } ] ] }, "\ud83d\udce5 Save Averages to Google Sheets": { "main": [ [ { "node": "\ud83e\uddfe Format Post Content", "type": "main", "index": 0 } ] ] }, "\ud83e\udd16 Agent: Fetch LinkedIn Posts (via MCP Tool)": { "main": [ [ { "node": "\ud83d\udcc8 Analyze Engagement Metrics", "type": "main", "index": 0 } ] ] } } }