AutomationFlowsAI & RAG › Notion to Pinecone Vector Store Integration

Notion to Pinecone Vector Store Integration

ByUdit Rawat @ailistmaster on n8n.io

This n8n automation is designed to extract, process, and store content from Notion pages into a Pinecone vector store. Here's a breakdown of the workflow:

Event trigger★★★★☆ complexityAI-powered8 nodesText Splitter Token SplitterNotion TriggerNotionDocument Default Data LoaderGoogle Gemini EmbeddingsPinecone Vector Store
AI & RAG Trigger: Event Nodes: 8 Complexity: ★★★★☆ AI nodes: yes Added:

This workflow corresponds to n8n.io template #2797 — we link there as the canonical source.

This workflow follows the Documentdefaultdataloader → Google Gemini Embeddings 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 →

Download .json
{
  "id": "vOSQYz747gtzj1zF",
  "meta": {
    "templateId": "2290"
  },
  "name": "Prod: Notion to Vector Store - Dimension 768",
  "tags": [
    {
      "id": "Vs70y1mj5s2XzUap",
      "name": "Production",
      "createdAt": "2024-12-24T14:42:00.549Z",
      "updatedAt": "2024-12-24T14:42:00.549Z"
    }
  ],
  "nodes": [
    {
      "id": "6d2579b8-376f-44c3-82e8-9dc608efd98b",
      "name": "Token Splitter",
      "type": "@n8n/n8n-nodes-langchain.textSplitterTokenSplitter",
      "position": [
        2200,
        800
      ],
      "parameters": {
        "chunkSize": 256,
        "chunkOverlap": 30
      },
      "typeVersion": 1
    },
    {
      "id": "79b3c147-08ca-4db4-9116-958a868cbfd9",
      "name": "Notion - Page Added Trigger",
      "type": "n8n-nodes-base.notionTrigger",
      "position": [
        1080,
        360
      ],
      "parameters": {
        "simple": false,
        "pollTimes": {
          "item": [
            {
              "mode": "everyMinute"
            }
          ]
        },
        "databaseId": {
          "__rl": true,
          "mode": "list",
          "value": "17b11930-c10f-8000-a545-ece7cade03f9",
          "cachedResultUrl": "https://www.notion.so/17b11930c10f8000a545ece7cade03f9",
          "cachedResultName": "Embeddings"
        }
      },
      "credentials": {
        "notionApi": {
          "name": "<your credential>"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "e4a6f524-e3f5-4d02-949a-8523f2d21965",
      "name": "Notion - Retrieve Page Content",
      "type": "n8n-nodes-base.notion",
      "position": [
        1300,
        360
      ],
      "parameters": {
        "blockId": {
          "__rl": true,
          "mode": "url",
          "value": "={{ $json.url }}"
        },
        "resource": "block",
        "operation": "getAll",
        "returnAll": true
      },
      "credentials": {
        "notionApi": {
          "name": "<your credential>"
        }
      },
      "typeVersion": 2.2
    },
    {
      "id": "bfebc173-8d4b-4f8f-a625-4622949dd545",
      "name": "Filter Non-Text Content",
      "type": "n8n-nodes-base.filter",
      "position": [
        1520,
        360
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 1,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
          },
          "combinator": "and",
          "conditions": [
            {
              "id": "e5b605e5-6d05-4bca-8f19-a859e474620f",
              "operator": {
                "type": "string",
                "operation": "notEquals"
              },
              "leftValue": "={{ $json.type }}",
              "rightValue": "image"
            },
            {
              "id": "c7415859-5ffd-4c78-b497-91a3d6303b6f",
              "operator": {
                "type": "string",
                "operation": "notEquals"
              },
              "leftValue": "={{ $json.type }}",
              "rightValue": "video"
            }
          ]
        }
      },
      "typeVersion": 2
    },
    {
      "id": "b04939f9-355a-430b-a069-b11800066313",
      "name": "Summarize - Concatenate Notion's blocks content",
      "type": "n8n-nodes-base.summarize",
      "position": [
        1780,
        360
      ],
      "parameters": {
        "options": {
          "outputFormat": "separateItems"
        },
        "fieldsToSummarize": {
          "values": [
            {
              "field": "content",
              "separateBy": "\n",
              "aggregation": "concatenate"
            }
          ]
        }
      },
      "typeVersion": 1
    },
    {
      "id": "0e64dbb5-20c1-4b90-b818-a1726aaf5112",
      "name": "Create metadata and load content",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "position": [
        2180,
        600
      ],
      "parameters": {
        "options": {
          "metadata": {
            "metadataValues": [
              {
                "name": "pageId",
                "value": "={{ $('Notion - Page Added Trigger').item.json.id }}"
              },
              {
                "name": "createdTime",
                "value": "={{ $('Notion - Page Added Trigger').item.json.created_time }}"
              },
              {
                "name": "pageTitle",
                "value": "={{ $('Notion - Page Added Trigger').item.json.properties.Name.title[0].text.content }}"
              }
            ]
          }
        },
        "jsonData": "={{ $json.concatenated_content }}",
        "jsonMode": "expressionData"
      },
      "typeVersion": 1
    },
    {
      "id": "1f93c3e6-2d53-46b4-9ce9-1350e660ba82",
      "name": "Embeddings Google Gemini",
      "type": "@n8n/n8n-nodes-langchain.embeddingsGoogleGemini",
      "position": [
        1940,
        580
      ],
      "parameters": {
        "modelName": "models/text-embedding-004"
      },
      "credentials": {
        "googlePalmApi": {
          "name": "<your credential>"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "b804b3fc-161c-40c1-ad9c-3022a09c4a0a",
      "name": "Pinecone Vector Store",
      "type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
      "position": [
        2060,
        360
      ],
      "parameters": {
        "mode": "insert",
        "options": {},
        "pineconeIndex": {
          "__rl": true,
          "mode": "list",
          "value": "notion-pages",
          "cachedResultName": "notion-pages"
        }
      },
      "credentials": {
        "pineconeApi": {
          "name": "<your credential>"
        }
      },
      "typeVersion": 1
    }
  ],
  "active": true,
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "245f016a-7538-4f45-94f0-d8b7e5c9c891",
  "connections": {
    "Token Splitter": {
      "ai_textSplitter": [
        [
          {
            "node": "Create metadata and load content",
            "type": "ai_textSplitter",
            "index": 0
          }
        ]
      ]
    },
    "Filter Non-Text Content": {
      "main": [
        [
          {
            "node": "Summarize - Concatenate Notion's blocks content",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Embeddings Google Gemini": {
      "ai_embedding": [
        [
          {
            "node": "Pinecone Vector Store",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "Notion - Page Added Trigger": {
      "main": [
        [
          {
            "node": "Notion - Retrieve Page Content",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Notion - Retrieve Page Content": {
      "main": [
        [
          {
            "node": "Filter Non-Text Content",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Create metadata and load content": {
      "ai_document": [
        [
          {
            "node": "Pinecone Vector Store",
            "type": "ai_document",
            "index": 0
          }
        ]
      ]
    },
    "Summarize - Concatenate Notion's blocks content": {
      "main": [
        [
          {
            "node": "Pinecone Vector Store",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}

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.

Pro

For the full experience including quality scoring and batch install features for each workflow upgrade to Pro

About this workflow

This n8n automation is designed to extract, process, and store content from Notion pages into a Pinecone vector store. Here's a breakdown of the workflow:

Source: https://n8n.io/workflows/2797/ — original creator credit. Request a take-down →

More AI & RAG workflows → · Browse all categories →

Related workflows

Workflows that share integrations, category, or trigger type with this one. All free to copy and import.

AI & RAG

Prod: Notion to Vector Store - Dimension 768. Uses textSplitterTokenSplitter, notionTrigger, notion, summarize. Event-driven trigger; 8 nodes.

Text Splitter Token Splitter, Notion Trigger, Notion +3
AI & RAG

This n8n template lets you automatically build and maintain an AI-ready knowledge base from Outlook emails and Notion pages. It stores both sources in a Pinecone vector database so your AI agent can r

Microsoft Outlook Trigger, Microsoft Outlook, Pinecone Vector Store +9
AI & RAG

Store Notion's Pages as Vector Documents into Supabase with OpenAI. Uses stickyNote, embeddingsOpenAi, textSplitterTokenSplitter, notionTrigger. Event-driven trigger; 9 nodes.

OpenAI Embeddings, Text Splitter Token Splitter, Notion Trigger +3
AI & RAG

Store Notion's Pages as Vector Documents into Supabase with OpenAI. Uses stickyNote, embeddingsOpenAi, textSplitterTokenSplitter, notionTrigger. Event-driven trigger; 9 nodes.

OpenAI Embeddings, Text Splitter Token Splitter, Notion Trigger +3
AI & RAG

This simple philosophy changes the way we think about automated sales agents. Context changes everything. In this 4-part workflow, we start by creating a knowledge base that will act as context across

Pinecone Vector Store, Document Default Data Loader, Text Splitter Recursive Character Text Splitter +12