MongoDB Agent

Empower your applications with intelligent data retrieval and interaction by deploying the MongoDB Agent workflow. This powerful n8n automation connects OpenAI's advanced language models with your MongoDB database, enabling dynamic, natural language queries and data manipulation. When a chat message is received via the "When chat message received" trigger, an "AI Agent - Movie Recommendation" node processes the input, leveraging an "OpenAI Chat Model" for understanding and response generation. It interacts with your MongoDB database using the "MongoDBAggregate" node to fetch relevant data and can even trigger an "insertFavorite" workflow via an "AI:toolWorkflow" node for specific actions, all while maintaining conversational context with a "Window Buffer Memory". This workflow is ideal for developers building customer support chatbots, data analysts needing quick insights from large datasets, or anyone looking to integrate AI-powered natural language interfaces directly with their MongoDB data, significantly reducing the manual effort of writing complex database queries and enhancing user experience through intuitive interactions.

8 nodesmanual trigger89 views0 copiesData

MongoDBOpenAI

Workflow JSON

{"id": "22PddLUgcjSJbT1w", "meta": {"instanceId": "fa7d5e2425ec76075df7100dbafffed91cc6f71f12fe92614bf78af63c54a61d", "templateCredsSetupCompleted": true}, "name": "MongoDB Agent", "tags": [], "nodes": [{"id": "d8c07efe-eca0-48cb-80e6-ea8117073c5f", "name": "OpenAI Chat Model", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "position": [1300, 560], "parameters": {"options": {}}, "credentials": {"openAiApi": {"id": "", "name": "[Your openAiApi]"}}, "typeVersion": 1}, {"id": "636de178-7b68-429a-9371-41cf2a950076", "name": "MongoDBAggregate", "type": "n8n-nodes-base.mongoDbTool", "position": [1640, 540], "parameters": {"query": "={{ $fromAI(\"pipeline\", \"The MongoDB pipeline to execute\" , \"string\" , [{\"$match\" : { \"rating\" : 5 } }])}}", "operation": "aggregate", "collection": "movies", "descriptionType": "manual", "toolDescription": "Get from AI the MongoDB Aggregation pipeline to get context based on the provided pipeline, the document structure of the documents is : {\n \"plot\": \"A group of bandits stage a brazen train hold-up, only to find a determined posse hot on their heels.\",\n \"genres\": [\n \"Short\",\n \"Western\"\n ],\n \"runtime\": 11,\n \"cast\": [\n \"A.C. Abadie\",\n \"Gilbert M. 'Broncho Billy' Anderson\",\n ...\n ],\n \"poster\": \"...jpg\",\n \"title\": \"The Great Train Robbery\",\n \"fullplot\": \"Among the earliest existing films in American cinema - notable as the ...\",\n \"languages\": [\n \"English\"\n ],\n \"released\": \"date\"\n },\n \"directors\": [\n \"Edwin S. Porter\"\n ],\n \"rated\": \"TV-G\",\n \"awards\": {\n \"wins\": 1,\n \"nominations\": 0,\n \"text\": \"1 win.\"\n },\n \"lastupdated\": \"2015-08-13 00:27:59.177000000\",\n \"year\": 1903,\n \"imdb\": {\n \"rating\": 7.4,"}, "credentials": {"mongoDb": {"id": "", "name": "[Your mongoDb]"}}, "typeVersion": 1.1}, {"id": "e0f248dc-22b7-40a2-a00e-6298b51e4470", "name": "Window Buffer Memory", "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow", "position": [1500, 540], "parameters": {"contextWindowLength": 10}, "typeVersion": 1.2}, {"id": "da27ee52-43db-4818-9844-3c0a064bf958", "name": "When chat message received", "type": "@n8n/n8n-nodes-langchain.chatTrigger", "position": [1160, 400], "webhookId": "0730df2d-2f90-45e0-83dc-609668260fda", "parameters": {"mode": "webhook", "public": true, "options": {"allowedOrigins": "*"}}, "typeVersion": 1.1}, {"id": "9ad79da9-3145-44be-9026-e37b0e856f5d", "name": "insertFavorite", "type": "@n8n/n8n-nodes-langchain.toolWorkflow", "position": [1860, 520], "parameters": {"name": "insertFavorites", "workflowId": {"__rl": true, "mode": "list", "value": "6QuKnOrpusQVu66Q", "cachedResultName": "insertMongoDB"}, "description": "=Use this tool only to add favorites with the structure of {\"title\" : \"recieved title\" }"}, "typeVersion": 1.2}, {"id": "4d7713d1-d2ad-48bf-971b-b86195e161ca", "name": "AI Agent - Movie Recommendation", "type": "@n8n/n8n-nodes-langchain.agent", "position": [1380, 300], "parameters": {"text": "=Assistant for best movies context, you have tools to search using \"MongoDBAggregate\" and you need to provide a MongoDB aggregation pipeline code array as a \"query\" input param. User input and request: {{ $json.chatInput }}. Only when a user confirms a favorite movie use the insert favorite using the \"insertFavorite\" workflow tool of to insertFavorite as { \"title\" : \"<TITLE>\" }.", "options": {}, "promptType": "define"}, "typeVersion": 1.7}, {"id": "2eac8aed-9677-4d89-bd76-456637f5b979", "name": "Sticky Note", "type": "n8n-nodes-base.stickyNote", "position": [880, 300], "parameters": {"width": 216.0875923062025, "height": 499.89779507612025, "content": "## AI Agent powered by OpenAI and MongoDB \n\nThis flow is designed to work as an AI autonomous agent that can get chat messages, query data from MongoDB using the aggregation framework.\n\nFollowing by augmenting the results from the sample movies collection and allowing storing my favorite movies back to the database using an \"insert\" flow. "}, "typeVersion": 1}, {"id": "4d8130fe-4aed-4e09-9c1d-60fb9ac1a500", "name": "Sticky Note1", "type": "n8n-nodes-base.stickyNote", "position": [1300, 720], "parameters": {"content": "## Process\n\nThe message is being processed by the \"Chat Model\" and the correct tool is used according to the message. "}, "typeVersion": 1}], "active": true, "pinData": {}, "settings": {"executionOrder": "v1"}, "versionId": "879aab24-6346-435f-8fd4-3fca856ba64c", "connections": {"insertFavorite": {"ai_tool": [[{"node": "AI Agent - Movie Recommendation", "type": "ai_tool", "index": 0}]]}, "MongoDBAggregate": {"ai_tool": [[{"node": "AI Agent - Movie Recommendation", "type": "ai_tool", "index": 0}]]}, "OpenAI Chat Model": {"ai_languageModel": [[{"node": "AI Agent - Movie Recommendation", "type": "ai_languageModel", "index": 0}]]}, "Window Buffer Memory": {"ai_memory": [[{"node": "AI Agent - Movie Recommendation", "type": "ai_memory", "index": 0}]]}, "When chat message received": {"main": [[{"node": "AI Agent - Movie Recommendation", "type": "main", "index": 0}]]}}}

How to Import This Workflow

1Copy the workflow JSON above using the Copy Workflow JSON button.
2Open your n8n instance and go to Workflows.
3Click Import from JSON and paste the copied workflow.

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