Back to Catalog

Binance spot trader - limit & market orders via API

Todsaporn SangboonTodsaporn Sangboon
16507 views
2/3/2026
Official Page

๐Ÿ“ˆ How it works

This n8n workflow allows you to interact with Binance Spot Trading API directly to:

  • Place Limit Buy and Limit Sell orders
  • Place Market Buy and Market Sell orders
  • Query account info and open orders
  • Cancel all open orders for a specific symbol

All requests are signed using Binance's HMAC SHA256 signature method for secure trading.


โš™๏ธ Setup Steps

  1. Create Binance API Credentials in n8n:

    • Go to Credentials > New
    • Choose Binance API
    • Add api_key and api_secret
    • Save as Binance API
  2. Import this workflow into your n8n instance.

  3. Update default values:

    • In Set Parameter nodes like LimitBuy Parameter, change:
      • symbol (e.g. BTCUSDT)
      • quantity, price as needed
  4. Run the workflow manually via the Execute workflow trigger.


โœ… Notes

  • Credential node is marked with instructions.
  • HMAC signatures are automatically calculated before making each request.
  • HTTP nodes are preconfigured for Binance API v3.

๐Ÿ”’ No API key or secret is included.

Binance Spot Trader - Limit/Market Orders via API

This n8n workflow provides a basic framework for interacting with a cryptocurrency exchange API, specifically for placing orders. It demonstrates how to prepare data, sign requests using cryptographic functions, and make an HTTP request to an API endpoint.

What it does

This workflow is designed to illustrate the core components needed for programmatic trading via an API.

  1. Manual Trigger: The workflow is initiated manually, allowing for on-demand execution.
  2. Edit Fields (Set): This node is intended for defining and preparing the necessary parameters for an API request, such as API keys, secrets, and order details. (Note: The provided JSON does not contain specific field definitions, so these would need to be configured by the user).
  3. Crypto: This node is used to sign the API request, which is a common security requirement for many cryptocurrency exchange APIs. It likely performs HMAC-SHA256 hashing using the secret key.
  4. Code: A custom JavaScript code node is included, which would typically be used for complex data manipulation, constructing the final API endpoint URL, or adding specific headers required by the exchange.
  5. HTTP Request: This node makes the actual API call to the exchange's endpoint with the prepared data and signature.

Prerequisites/Requirements

  • n8n Instance: A running n8n instance to import and execute the workflow.
  • Cryptocurrency Exchange Account: An account with a cryptocurrency exchange that offers API access (e.g., Binance, as hinted by the directory name).
  • API Key and Secret: API credentials (key and secret) generated from your exchange account, with appropriate permissions for trading.
  • Understanding of Exchange API Documentation: Familiarity with the specific API endpoints, parameters, and signing mechanisms of your chosen exchange.

Setup/Usage

  1. Import the Workflow: Import the provided JSON into your n8n instance.
  2. Configure Credentials:
    • Open the "Edit Fields (Set)" node. You will need to add your exchange's API Key and Secret here, and any other relevant order parameters (e.g., symbol, side, type, quantity, price).
    • Ensure the "Crypto" node is configured with the correct algorithm (e.g., HMAC-SHA256) and uses your API Secret to sign the request.
  3. Configure Code Node:
    • Review and modify the "Code" node to construct the request body, query parameters, and headers according to your exchange's API documentation. This is where you'd typically build the full URL and payload.
  4. Configure HTTP Request Node:
    • Set the correct API endpoint URL for your chosen exchange (e.g., Binance spot trading API).
    • Configure the HTTP method (e.g., POST for placing orders).
    • Add any necessary headers (e.g., X-MBX-APIKEY for Binance).
    • Ensure the request body is correctly passed from previous nodes.
  5. Test the Workflow: Execute the workflow manually to test the API call. Start with testnet environments if available before using real funds.

Note: This workflow is a foundational template. You will need to populate the "Edit Fields (Set)" and "Code" nodes with specific values and logic based on the cryptocurrency exchange's API documentation you intend to use. This includes defining the exact API endpoint, request parameters (e.g., symbol, side, type, quantity, price), and the precise method for generating the signature.

Related Templates

Track competitor SEO keywords with Decodo + GPT-4.1-mini + Google Sheets

This workflow automates competitor keyword research using OpenAI LLM and Decodo for intelligent web scraping. Who this is for SEO specialists, content strategists, and growth marketers who want to automate keyword research and competitive intelligence. Marketing analysts managing multiple clients or websites who need consistent SEO tracking without manual data pulls. Agencies or automation engineers using Google Sheets as an SEO data dashboard for keyword monitoring and reporting. What problem this workflow solves Tracking competitor keywords manually is slow and inconsistent. Most SEO tools provide limited API access or lack contextual keyword analysis. This workflow solves that by: Automatically scraping any competitorโ€™s webpage with Decodo. Using OpenAI GPT-4.1-mini to interpret keyword intent, density, and semantic focus. Storing structured keyword insights directly in Google Sheets for ongoing tracking and trend analysis. What this workflow does Trigger โ€” Manually start the workflow or schedule it to run periodically. Input Setup โ€” Define the website URL and target country (e.g., https://dev.to, france). Data Scraping (Decodo) โ€” Fetch competitor web content and metadata. Keyword Analysis (OpenAI GPT-4.1-mini) Extract primary and secondary keywords. Identify focus topics and semantic entities. Generate a keyword density summary and SEO strength score. Recommend optimization and internal linking opportunities. Data Structuring โ€” Clean and convert GPT output into JSON format. Data Storage (Google Sheets) โ€” Append structured keyword data to a Google Sheet for long-term tracking. Setup Prerequisites If you are new to Decode, please signup on this link visit.decodo.com n8n account with workflow editor access Decodo API credentials OpenAI API key Google Sheets account connected via OAuth2 Make sure to install the Decodo Community node. Create a Google Sheet Add columns for: primarykeywords, seostrengthscore, keyworddensity_summary, etc. Share with your n8n Google account. Connect Credentials Add credentials for: Decodo API credentials - You need to register, login and obtain the Basic Authentication Token via Decodo Dashboard OpenAI API (for GPT-4o-mini) Google Sheets OAuth2 Configure Input Fields Edit the โ€œSet Input Fieldsโ€ node to set your target site and region. Run the Workflow Click Execute Workflow in n8n. View structured results in your connected Google Sheet. How to customize this workflow Track Multiple Competitors โ†’ Use a Google Sheet or CSV list of URLs; loop through them using the Split In Batches node. Add Language Detection โ†’ Add a Gemini or GPT node before keyword analysis to detect content language and adjust prompts. Enhance the SEO Report โ†’ Expand the GPT prompt to include backlink insights, metadata optimization, or readability checks. Integrate Visualization โ†’ Connect your Google Sheet to Looker Studio for SEO performance dashboards. Schedule Auto-Runs โ†’ Use the Cron Node to run weekly or monthly for competitor keyword refreshes. Summary This workflow automates competitor keyword research using: Decodo for intelligent web scraping OpenAI GPT-4.1-mini for keyword and SEO analysis Google Sheets for live tracking and reporting Itโ€™s a complete AI-powered SEO intelligence pipeline ideal for teams that want actionable insights on keyword gaps, optimization opportunities, and content focus trends, without relying on expensive SEO SaaS tools.

Ranjan DailataBy Ranjan Dailata
161

Generate song lyrics and music from text prompts using OpenAI and Fal.ai Minimax

Spark your creativity instantly in any chatโ€”turn a simple prompt like "heartbreak ballad" into original, full-length lyrics and a professional AI-generated music track, all without leaving your conversation. ๐Ÿ“‹ What This Template Does This chat-triggered workflow harnesses AI to generate detailed, genre-matched song lyrics (at least 600 characters) from user messages, then queues them for music synthesis via Fal.ai's minimax-music model. It polls asynchronously until the track is ready, delivering lyrics and audio URL back in chat. Crafts original, structured lyrics with verses, choruses, and bridges using OpenAI Submits to Fal.ai for melody, instrumentation, and vocals aligned to the style Handles long-running generations with smart looping and status checks Returns complete song package (lyrics + audio link) for seamless sharing ๐Ÿ”ง Prerequisites n8n account (self-hosted or cloud with chat integration enabled) OpenAI account with API access for GPT models Fal.ai account for AI music generation ๐Ÿ”‘ Required Credentials OpenAI API Setup Go to platform.openai.com โ†’ API keys (sidebar) Click "Create new secret key" โ†’ Name it (e.g., "n8n Songwriter") Copy the key and add to n8n as "OpenAI API" credential type Test by sending a simple chat completion request Fal.ai HTTP Header Auth Setup Sign up at fal.ai โ†’ Dashboard โ†’ API Keys Generate a new API key โ†’ Copy it In n8n, create "HTTP Header Auth" credential: Name="Fal.ai", Header Name="Authorization", Header Value="Key [Your API Key]" Test with a simple GET to their queue endpoint (e.g., /status) โš™๏ธ Configuration Steps Import the workflow JSON into your n8n instance Assign OpenAI API credentials to the "OpenAI Chat Model" node Assign Fal.ai HTTP Header Auth to the "Generate Music Track", "Check Generation Status", and "Fetch Final Result" nodes Activate the workflowโ€”chat trigger will appear in your n8n chat interface Test by messaging: "Create an upbeat pop song about road trips" ๐ŸŽฏ Use Cases Content Creators: YouTubers generating custom jingles for videos on the fly, streamlining production from idea to audio export Educators: Music teachers using chat prompts to create era-specific folk tunes for classroom discussions, fostering interactive learning Gift Personalization: Friends crafting anniversary R&B tracks from shared memories via quick chats, delivering emotional audio surprises Artist Brainstorming: Songwriters prototyping hip-hop beats in real-time during sessions, accelerating collaboration and iteration โš ๏ธ Troubleshooting Invalid JSON from AI Agent: Ensure the system prompt stresses valid JSON; test the agent standalone with a sample query Music Generation Fails (401/403): Verify Fal.ai API key has minimax-music access; check usage quotas in dashboard Status Polling Loops Indefinitely: Bump wait time to 45-60s for complex tracks; inspect fal.ai queue logs for bottlenecks Lyrics Under 600 Characters: Tweak agent prompt to enforce fuller structures like [V1][C][V2][B][C]; verify output length in executions

Daniel NkenchoBy Daniel Nkencho
601

Automate invoice processing with OCR, GPT-4 & Salesforce opportunity creation

PDF Invoice Extractor (AI) End-to-end pipeline: Watch Drive โžœ Download PDF โžœ OCR text โžœ AI normalize to JSON โžœ Upsert Buyer (Account) โžœ Create Opportunity โžœ Map Products โžœ Create OLI via Composite API โžœ Archive to OneDrive. --- Node by node (what it does & key setup) 1) Google Drive Trigger Purpose: Fire when a new file appears in a specific Google Drive folder. Key settings: Event: fileCreated Folder ID: google drive folder id Polling: everyMinute Creds: googleDriveOAuth2Api Output: Metadata { id, name, ... } for the new file. --- 2) Download File From Google Purpose: Get the file binary for processing and archiving. Key settings: Operation: download File ID: ={{ $json.id }} Creds: googleDriveOAuth2Api Output: Binary (default key: data) and original metadata. --- 3) Extract from File Purpose: Extract text from PDF (OCR as needed) for AI parsing. Key settings: Operation: pdf OCR: enable for scanned PDFs (in options) Output: JSON with OCR text at {{ $json.text }}. --- 4) Message a model (AI JSON Extractor) Purpose: Convert OCR text into strict normalized JSON array (invoice schema). Key settings: Node: @n8n/n8n-nodes-langchain.openAi Model: gpt-4.1 (or gpt-4.1-mini) Message role: system (the strict prompt; references {{ $json.text }}) jsonOutput: true Creds: openAiApi Output (per item): $.message.content โ†’ the parsed JSON (ensure itโ€™s an array). --- 5) Create or update an account (Salesforce) Purpose: Upsert Buyer as Account using an external ID. Key settings: Resource: account Operation: upsert External Id Field: taxid_c External Id Value: ={{ $json.message.content.buyer.tax_id }} Name: ={{ $json.message.content.buyer.name }} Creds: salesforceOAuth2Api Output: Account record (captures Id) for downstream Opportunity. --- 6) Create an opportunity (Salesforce) Purpose: Create Opportunity linked to the Buyer (Account). Key settings: Resource: opportunity Name: ={{ $('Message a model').item.json.message.content.invoice.code }} Close Date: ={{ $('Message a model').item.json.message.content.invoice.issue_date }} Stage: Closed Won Amount: ={{ $('Message a model').item.json.message.content.summary.grand_total }} AccountId: ={{ $json.id }} (from Upsert Account output) Creds: salesforceOAuth2Api Output: Opportunity Id for OLI creation. --- 7) Build SOQL (Code / JS) Purpose: Collect unique product codes from AI JSON and build a SOQL query for PricebookEntry by Pricebook2Id. Key settings: pricebook2Id (hardcoded in script): e.g., 01sxxxxxxxxxxxxxxx Source lines: $('Message a model').first().json.message.content.products Output: { soql, codes } --- 8) Query PricebookEntries (Salesforce) Purpose: Fetch PricebookEntry.Id for each Product2.ProductCode. Key settings: Resource: search Query: ={{ $json.soql }} Creds: salesforceOAuth2Api Output: Items with Id, Product2.ProductCode (used for mapping). --- 9) Code in JavaScript (Build OLI payloads) Purpose: Join lines with PBE results and Opportunity Id โžœ build OpportunityLineItem payloads. Inputs: OpportunityId: ={{ $('Create an opportunity').first().json.id }} Lines: ={{ $('Message a model').first().json.message.content.products }} PBE rows: from previous node items Output: { body: { allOrNone:false, records:[{ OpportunityLineItem... }] } } Notes: Converts discount_total โžœ per-unit if needed (currently commented for standard pricing). Throws on missing PBE mapping or empty lines. --- 10) Create Opportunity Line Items (HTTP Request) Purpose: Bulk create OLIs via Salesforce Composite API. Key settings: Method: POST URL: https://<your-instance>.my.salesforce.com/services/data/v65.0/composite/sobjects Auth: salesforceOAuth2Api (predefined credential) Body (JSON): ={{ $json.body }} Output: Composite API results (per-record statuses). --- 11) Update File to One Drive Purpose: Archive the original PDF in OneDrive. Key settings: Operation: upload File Name: ={{ $json.name }} Parent Folder ID: onedrive folder id Binary Data: true (from the Download node) Creds: microsoftOneDriveOAuth2Api Output: Uploaded file metadata. --- Data flow (wiring) Google Drive Trigger โ†’ Download File From Google Download File From Google โ†’ Extract from File โ†’ Update File to One Drive Extract from File โ†’ Message a model Message a model โ†’ Create or update an account Create or update an account โ†’ Create an opportunity Create an opportunity โ†’ Build SOQL Build SOQL โ†’ Query PricebookEntries Query PricebookEntries โ†’ Code in JavaScript Code in JavaScript โ†’ Create Opportunity Line Items --- Quick setup checklist ๐Ÿ” Credentials: Connect Google Drive, OneDrive, Salesforce, OpenAI. ๐Ÿ“‚ IDs: Drive Folder ID (watch) OneDrive Parent Folder ID (archive) Salesforce Pricebook2Id (in the JS SOQL builder) ๐Ÿง  AI Prompt: Use the strict system prompt; jsonOutput = true. ๐Ÿงพ Field mappings: Buyer tax id/name โ†’ Account upsert fields Invoice code/date/amount โ†’ Opportunity fields Product name must equal your Product2.ProductCode in SF. โœ… Test: Drop a sample PDF โ†’ verify: AI returns array JSON only Account/Opportunity created OLI records created PDF archived to OneDrive --- Notes & best practices If PDFs are scans, enable OCR in Extract from File. If AI returns non-JSON, keep โ€œReturn only a JSON arrayโ€ as the last line of the prompt and keep jsonOutput enabled. Consider adding validation on parsing.warnings to gate Salesforce writes. For discounts/taxes in OLI: Standard OLI fields donโ€™t support per-line discount amounts directly; model them in UnitPrice or custom fields. Replace the Composite API URL with your orgโ€™s domain or use the Salesforce nodeโ€™s Bulk Upsert for simplicity.

Le NguyenBy Le Nguyen
942