Telegram trading bot assistant | LLM powered trading bot for crypto/forex
Needs changesNeeds changes. This template uses 1 thing(s) that n8n 3.0 removes: AI Agent v1 (old agent modes). 1 breaking item(s) found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 7 nodes and runs on Telegram events. Along the way it connects Telegram, MongoDB Chat Memory, HTTP Request and Google Gemini Chat Model.
How it runs
Trigger: On Telegram events.
- AI Agent: runs an AI agent, with model: Google Gemini Chat Model; 2 tools (Real Time Price, Get Price History); memory: MongoDB Chat Memory
- Send a text message (Telegram): uses Telegram
Services it uses
Before you upgrade to n8n 3.0
1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:
- AI Agent v1 (old agent modes) in AI Agent1 (v1.9): replace with Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.
Rather not rewrite it? Many of these flows can be rebuilt in Make (free plan).
| Removed in 3.0 | Replace with |
|---|---|
| AI Agent v1 (old agent modes) AI Agent1 (v1.9) | Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent. |
Nodes used (6)
- Telegram Trigger
n8n-nodes-base.telegramTrigger - MongoDB Chat Memory
@n8n/n8n-nodes-langchain.memoryMongoDbChat - Telegram
n8n-nodes-base.telegram - AI Agent
@n8n/n8n-nodes-langchain.agent - Http Request Tool
n8n-nodes-base.httpRequestTool - Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini
From the author
Purpose & Audience This n8n workflow telegram bot is designed for crypto, forex and stock traders, quantitative analysts, and AI enthusiasts who want to explore how different Large Language Models (LLMs) perform in real-world trading scenarios. Inspired by…