Api schema extractor

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

This workflow automates the process of discovering and extracting APIs from various services, followed by generating custom schemas. It works in three distinct stages: research, extraction, and sch...

Best for

Engineering automation workflows
AI RAG automation workflows
advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.manualtrigger, n8n-nodes-base.httprequest, n8n-nodes-base.splitout, @n8n/n8n-nodes-langchain.textsplitterrecursivecharactertextsplitter, n8n-nodes-base.set, @n8n/n8n-nodes-langchain.documentdefaultdataloader, n8n-nodes-base.executeworkflowtrigger, n8n-nodes-base.executiondata

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Polina Medvedieva.

Original n8n.io source

1.1 Workflow description

Title: Api schema extractor
Workflow name: Api schema extractor

🙏 Jim Le deserves major kudos for helping to build this sophisticated three-stage workflow that cleverly automates API documentation processing using a smart combination of web scraping, vector search, and LLM technologies.

How it works

Stage 1 - Research:

Fetches pending services from a Google Sheet
Uses Google search to find API documentation
Employs Apify for web scraping to filter relevant pages
Stores webpage contents and metadata in Qdrant (vector database)
Updates progress status in Google Sheet (pending, ok, or error)

Stage 2 - Extraction:

Processes services that completed research successfully
Queries vector store to identify products and offerings
Further queries for relevant API documentation
Uses Gemini (LLM) to extract API operations
Records extracted operations in Google Sheet
Updates progress status (pending, ok, or error)

Stage 3 - Generation:

Takes services with successful extraction
Retrieves all API operations from the database
Combines and groups operations into a custom schema
Uploads final schema to Google Drive
Updates final status in sheet with file location

Ideal for:

Development teams needing to catalog multiple APIs
API documentation initiatives
Creating standardized API schema collections
Automating API discovery and documentation

Accounts required:

Google account (for Sheets and Drive access)
Apify account (for web scraping)
Qdrant database
Gemini API access

Set up instructions:

Prepare your Google Sheets document with the services information. Here's an example of a Google Sheet – you can copy it and change or remove the values under the columns. Also, make sure to update Google Sheets nodes with the correct Google Sheet ID.
Configure Google Sheets OAuth2 credentials, required third-party services (Apify, Qdrant) and Gemini.
Ensure proper permissions for Google Drive access.

1.2 Logical Blocks

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.

2. Block-by-Block Analysis

Block 1 - When clicking ‘Test workflow’

Type / Role: n8n-nodes-base.manualTrigger - manualTrigger
Config choices: Version 1

Block 2 - Web Search For API Schema

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 3 - Scrape Webpage Contents

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 4 - Results to List

Type / Role: n8n-nodes-base.splitOut - splitOut
Config choices: Version 1

Block 5 - Recursive Character Text Splitter1

Type / Role: @n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - textSplitterRecursiveCharacterTextSplitter
Config choices: Version 1

Block 6 - Content Chunking @ 50k Chars

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.3

Block 7 - Split Out Chunks

Type / Role: n8n-nodes-base.splitOut - splitOut
Config choices: Version 1

Block 8 - Default Data Loader

Type / Role: @n8n/n8n-nodes-langchain.documentDefaultDataLoader - documentDefaultDataLoader
Config choices: Version 1

Block 9 - Set Embedding Variables

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 10 - Execute Workflow Trigger

Type / Role: n8n-nodes-base.executeWorkflowTrigger - executeWorkflowTrigger
Config choices: Version 1

Block 11 - Execution Data

Type / Role: n8n-nodes-base.executionData - executionData
Config choices: Version 1

Block 12 - EventRouter

Type / Role: n8n-nodes-base.switch - switch
Config choices: Version 3.2

Block 13 - Google Gemini Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatGoogleGemini - lmChatGoogleGemini
Config choices: Version 1

Block 14 - Successful Runs

Type / Role: n8n-nodes-base.filter - filter
Config choices: Version 2.2

Block 15 - For Each Document...

Type / Role: n8n-nodes-base.splitInBatches - splitInBatches
Config choices: Version 3

Block 16 - Embeddings Google Gemini

Type / Role: @n8n/n8n-nodes-langchain.embeddingsGoogleGemini - embeddingsGoogleGemini
Config choices: Version 1

Block 17 - Has API Documentation?

Type / Role: @n8n/n8n-nodes-langchain.textClassifier - textClassifier
Config choices: Version 1

Block 18 - Store Document Embeddings

Type / Role: @n8n/n8n-nodes-langchain.vectorStoreQdrant - vectorStoreQdrant
Config choices: Version 1

Block 19 - Embeddings Google Gemini1

Type / Role: @n8n/n8n-nodes-langchain.embeddingsGoogleGemini - embeddingsGoogleGemini
Config choices: Version 1

Block 20 - Google Gemini Chat Model1

Type / Role: @n8n/n8n-nodes-langchain.lmChatGoogleGemini - lmChatGoogleGemini
Config choices: Version 1

Block 21 - Extract API Operations

Type / Role: @n8n/n8n-nodes-langchain.informationExtractor - informationExtractor
Config choices: Version 1

Block 22 - Search in Relevant Docs

Type / Role: @n8n/n8n-nodes-langchain.vectorStoreQdrant - vectorStoreQdrant
Config choices: Version 1

Block 23 - Wait

Type / Role: n8n-nodes-base.wait - wait
Config choices: Version 1.1

Block 24 - Remove Dupes

Type / Role: n8n-nodes-base.removeDuplicates - removeDuplicates
Config choices: Version 2

Showing the first 24 of 88 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow	Api schema extractor
Complexity	advanced
Nodes	88
Categories	Engineering, AI RAG
Author	Polina Medvedieva
Published	19 Dec 2024

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/2658/2658.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

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.

Download workflow JSON Original n8n.io source Engineering workflows AI RAG workflows

Frequently asked questions

What does Api schema extractor do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

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 RAG use case.

Polina Medvedieva

3 workflows

Nodes

n8n-nodes-base.manualtrigger n8n-nodes-base.httprequest n8n-nodes-base.splitout @n8n/n8n-nodes-langchain.textsplitterrecursivecharactertextsplitter n8n-nodes-base.set @n8n/n8n-nodes-langchain.documentdefaultdataloader n8n-nodes-base.executeworkflowtrigger n8n-nodes-base.executiondata

Complexity

advanced

Published 19 Dec 2024

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/2658/2658.json

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Api schema extractor

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

How it works

Stage 1 - Research:

Stage 2 - Extraction:

Stage 3 - Generation:

Ideal for:

Accounts required:

Set up instructions:

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - When clicking ‘Test workflow’

Block 2 - Web Search For API Schema

Block 3 - Scrape Webpage Contents

Block 4 - Results to List

Block 5 - Recursive Character Text Splitter1

Block 6 - Content Chunking @ 50k Chars

Block 7 - Split Out Chunks

Block 8 - Default Data Loader

Block 9 - Set Embedding Variables

Block 10 - Execute Workflow Trigger

Block 11 - Execution Data

Block 12 - EventRouter

Block 13 - Google Gemini Chat Model

Block 14 - Successful Runs

Block 15 - For Each Document...

Block 16 - Embeddings Google Gemini

Block 17 - Has API Documentation?

Block 18 - Store Document Embeddings

Block 19 - Embeddings Google Gemini1

Block 20 - Google Gemini Chat Model1

Block 21 - Extract API Operations

Block 22 - Search in Relevant Docs

Block 23 - Wait

Block 24 - Remove Dupes

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions