+4
Get Real-time Crypto Token Insights via Telegram with DexScreener and GPT-4o
Published 5 days ago
Created by
Don Jayamaha Jr
Template description
Instantly access real-time decentralized exchange (DEX) insights directly in Telegram! This workflow integrates the DexScreener API with GPT-4o-powered AI and Telegram, allowing users to fetch the latest blockchain token analytics, liquidity pools, and trending tokens effortlessly. Ideal for crypto traders, DeFi analysts, and investors who need actionable market data at their fingertips.
How It Works
- A Telegram bot listens for user queries about tokens or trading pairs.
- The workflow interacts with the DexScreener API (no API key required) to fetch real-time data, including:
- Token fundamentals (profiles, images, descriptions, and links)
- Trending and boosted tokens (hyped projects, potential market movers)
- Trading pair analytics (liquidity, price action, volumes, volatility)
- Order and payment activity (transaction insights, investor movements)
- Liquidity pool depth (market stability, capital flows)
- Multi-chain pair comparisons (performance tracking across networks)
- An AI-powered language model (GPT-4o-mini) enhances responses for better insights.
- The workflow logs session data to improve user interaction tracking.
- The requested DEX insights are sent back via Telegram in an easy-to-read format.
What You Can Do with This Agent
This AI-driven Telegram bot enables you to:
✅ Track trending and boosted tokens before they gain mainstream traction.
✅ Monitor real-time liquidity pools to assess token stability.
✅ Analyze active trading pairs across different blockchains.
✅ Identify transaction trends by checking paid orders for tokens.
✅ Compare market activity with detailed trading pair analysis.
✅ Receive instant insights with AI-enhanced responses for deeper understanding.
Set Up Steps
- Create a Telegram Bot
- Use @BotFather on Telegram to create a bot and obtain an API token.
- Configure Telegram API Credentials in n8n
- Add your Telegram bot token under Telegram API credentials.
- Deploy and Test
- Send a query (e.g.,
"SOL/USDC") to your Telegram bot and receive real-time insights instantly!
- Send a query (e.g.,
🚀 Unlock powerful, real-time DEX insights directly in Telegram—no API key required!
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+7
Build Your First AI Data Analyst Chatbot
Enhance your data analysis by connecting an AI Agent to your dataset, using n8n tools.
This template teaches you how to build an AI Data Analyst Chatbot that is capable of pulling data from your sources, using tools like Google Sheets or databases. It's designed to be easy and efficient, making it a good starting point for AI-driven data analysis.
You can easily replace the current Google Sheets tools for databases like Postgres or MySQL.
How It Works
The core of the workflow is the AI Agent. It's connected to different data retrieval tools, to get data from Google Sheets (or your preferred database) in many different ways.
Once the data is retrieved, the Calculator tool allows the AI to perform mathematical operations, making your data analysis precise.
Who is this template for
Data Analysts & Researchers:** Pull data from different sources and perform quick calculations.
Developers & AI Enthusiasts:** Learn to build your first AI Agent with easy dataset access.
Business Owners:** Streamline your data analysis with AI insights and automate repetitive tasks.
Automation Experts:** Enhance your automation skills by integrating AI with your existing databases.
How to Set Up
You can find detailed instructions in the workflow itself.
Check out my other templates
👉 https://n8n.io/creators/solomon/
Solomon
+10
Invoice data extraction with LlamaParse and OpenAI
This n8n workflow automates the process of parsing and extracting data from PDF invoices. With this workflow, accounts and finance people can realise huge time and cost savings in their busy schedules.
Read the Blog: https://blog.n8n.io/how-to-extract-data-from-pdf-to-excel-spreadsheet-advance-parsing-with-n8n-io-and-llamaparse/
How it works
This workflow will watch an email inbox for incoming invoices from suppliers
It will download the attached PDFs and processing them through a third party service called LlamaParse.
LlamaParse is specifically designed to handle and convert complex PDF data structures such as tables to markdown.
Markdown is easily to process for LLM models and so the data extraction by our AI agent is more accurate and reliable.
The workflow exports the extracted data from the AI agent to Google Sheets once the job complete.
Requirements
The criteria of the email trigger must be configured to capture emails with attachments.
The gmail label "invoice synced" must be created before using this workflow.
A LlamaIndex.ai account to use the LlamaParse service.
An OpenAI account to use GPT for AI work.
Google Sheets to save the output of the data extraction process although this can be replaced for whatever your needs.
Customizing this workflow
This workflow uses Gmail and Google Sheets but these can easily be swapped out for equivalent services such as Outlook and Excel.
Not using Excel? Simple redirect the output of the AI agent to your accounting software of choice.
Jimleuk
+9
Actioning Your Meeting Next Steps using Transcripts and AI
This n8n workflow demonstrates how you can summarise and automate post-meeting actions from video transcripts fed into an AI Agent.
Save time between meetings by allowing AI handle the chores of organising follow-up meetings and invites.
How it works
This workflow scans for the calendar for client or team meetings which were held online. * Attempts will be made to fetch any recorded transcripts which are then sent to the AI agent.
The AI agent summarises and identifies if any follow-on meetings are required.
If found, the Agent will use its Calendar Tool to to create the event for the time, date and place for the next meeting as well as add known attendees.
Requirements
Google Calendar and the ability to fetch Meeting Transcripts (There is a special OAuth permission for this action!)
OpenAI account for access to the LLM.
Customising the workflow
This example only books follow-on meetings but could be extended to generate reports or send emails.
Jimleuk
Analyze tradingview.com charts with Chrome extension, N8N and OpenAI
This flow is supported by a Chrome plugin created with Cursor AI.
The idea was to create a Chrome plugin and a backend service in N8N to do chart analytics with OpenAI. It's a good sample on how to submit a screenshot from the browser to N8N.
Who is it for?
N8N developers who want to learn about using a Chrome plugin, an N8N webhook and OpenAI.
What opportunity does it present?
This sample opens up a whole range of N8N connected Chrome extensions that can analyze screenshots by using OpenAI.
What this workflow does?
The workflow contains:
a webhook trigger
an OpenAI node with GPT-4O-MINI and Analyze Image selected
a response node to send back the Text that was created after analysing the screenshot.
All this is needed to talk to the Chrome extension which is created with Cursor AI.
The idea is to visit the tradingview.com crypto charts, click the Chrome plugin and get back analytics about the shown chart in understandable language. This is driven by the N8N flow.
With the new image analytics capabilities of OpenAI this opens up a world of opportunities.
Requirements/setup
OpenAI API key
Cursor AI installed
The Chrome extension. Download
The N8N JSON code. Download
How to customize it to your needs?
Both the Chrome extension and N8N flow can be adapted to use on other websites. You can consider:
analyzing a financial screen and ask questions about the data shown
analyzing other charts
extending the N8N workflow with other AI nodes
With AI and image analytics the sky is the limit and in some cases it saves you from creating complex API integrations.
Download Chrome extension
Hans Blaauw
+11
Build a Financial Documents Assistant using Qdrant and Mistral.ai
This n8n workflow demonstrates how to manage your Qdrant vector store when there is a need to keep it in sync with local files. It covers creating, updating and deleting vector store records ensuring our chatbot assistant is never outdated or misleading.
Disclaimer
This workflow depends on local files accessed through the local filesystem and so will only work on a self-hosted version of n8n at this time. It is possible to amend this workflow to work on n8n cloud by replacing the local file trigger and read file nodes.
How it works
A local directory where bank statements are downloaded to is monitored via a local file trigger. The trigger watches for the file create, file changed and file deleted events.
When a file is created, its contents are uploaded to the vector store.
When a file is updated, its previous records are replaced.
When the file is deleted, the corresponding records are also removed from the vector store.
A simple Question and Answer Chatbot is setup to answer any questions about the bank statements in the system.
Requirements
A self-hosted version of n8n. Some of the nodes used in this workflow only work with the local filesystem.
Qdrant instance to store the records.
Customising the workflow
This workflow can also work with remote data. Try integrating accounting or CRM software to build a managed system for payroll, invoices and more.
Want to go fully local?
A version of this workflow is available which uses Ollama instead. You can download this template here: https://drive.google.com/file/d/189F1fNOiw6naNSlSwnyLVEm_Ho_IFfdM/view?usp=sharing
Jimleuk
+7
Invoices from Gmail to Drive and Google Sheets
Attachments Gmail to Drive and Google Sheets
Description
Automatically process invoice emails by saving attachments to Google Drive and extracting key invoice data to Google Sheets using AI. This workflow monitors your Gmail for unread emails with attachments, saves PDFs to a specified Google Drive folder, and uses OpenAI's GPT-4o to extract invoice details (date, description, amount) into a structured spreadsheet.
Use cases
Invoice Management**: Automatically organize and track invoices received via email
Financial Record Keeping**: Maintain a structured database of all invoice information
Document Organization**: Keep digital copies of invoices organized in Google Drive
Automated Data Entry**: Eliminate manual data entry for invoice processing
Resources
Gmail account
Google Drive account
Google Sheets account
OpenAI API key
Setup instructions
Prerequisites
Active Gmail, Google Drive, and Google Sheets accounts
OpenAI API key (GPT-4o model access)
n8n instance with credentials manager
Steps
Gmail and Google Drive Setup:
Connect your Gmail account in n8n credentials
Connect your Google Drive account with appropriate permissions
Create a destination folder in Google Drive for invoice storage
Google Sheets Setup:
Connect your Google Sheets account
Create a spreadsheet with columns: Invoice date, Invoice Description, Total price, and Fichero
Copy your spreadsheet ID for configuration
OpenAI Setup:
Add your OpenAI API key to n8n credentials
Configure Email Filter:
Update the email filter node to match your specific sender requirements
Benefits
Time Saving**: Eliminates manual downloading, filing, and data entry
Accuracy**: AI-powered data extraction reduces human error
Organization**: Consistent file naming and storage structure
Searchability**: Creates a searchable database of all invoice information
Automation**: Runs every minute to process new emails as they arrive
Related templates
Email Parser to CRM
Document Processing Workflow
Financial Data Automation
Juan Carlos Cavero Gracia
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+7
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+10
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The Agent's response is sent back to the user via the WhatsApp node.
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Requirements
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AI agent that can scrape webpages
⚙️🛠️🚀🤖🦾
This template is a PoC of a ReAct AI Agent capable of fetching random pages (not only Wikipedia or Google search results).
On the top part there's a manual chat node connected to a LangChain ReAct Agent. The agent has access to a workflow tool for getting page content.
The page content extraction starts with converting query parameters into a JSON object. There are 3 pre-defined parameters:
url** – an address of the page to fetch
method** = full / simplified
maxlimit** - maximum length for the final page. For longer pages an error message is returned back to the agent
Page content fetching is a multistep process:
An HTTP Request mode tries to get the page content.
If the page content was successfuly retrieved, a series of post-processing begin:
Extract HTML BODY; content
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The remaining content is sent back to an Agent if it's not too long (maxlimit = 70000 by default, see CONFIG node).
NB:
You can isolate the HTTP Request part into a separate workflow.
Check the Workflow Tool description, it guides the agent to provide a query string with several parameters instead of a JSON object.
Please reach out to Eduard is you need further assistance with you n8n workflows and automations!
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+2
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The workflow first populates a Pinecone index with vectors from a Bitcoin whitepaper. Then, it waits for a manual chat message. When received, the chat message is turned into a vector and compared to the vectors in Pinecone. The most similar vectors are retrieved and passed to OpenAI for generating a chat response.
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