Short-Term Trade Idea Generation
Ingests market data via MCP to generate structured short-term trade ideas with confidence scores and execution notes.
What it does
You get clean, structured short-term trade ideas complete with confidence scores and execution notes, automatically generated from real-time market data to help you spot momentum and catalysts quickly. The process filters out low-conviction setups so your downstream automation systems receive only high-quality JSON-ready insights for immediate action.
Step by step
- Configure the HTTP Request node to fetch real-time price data and volume metrics from a reliable market data provider.
- Set up the n8n workflow to parse the incoming JSON payload and map specific fields like ticker, current price, and moving averages for analysis.
- Define the Google Sheets structure with columns for timestamp, asset symbol, thesis summary, confidence score, and execution notes.
Where the LLM does the work
- Prompt the OpenAI API to synthesize market context into a concise trade thesis that includes momentum indicators and potential catalysts.
- Instruct the model to assign a numerical confidence score between 0 and 100 based on the strength of the identified signals.
- Have the LLM generate specific execution notes such as entry price targets, stop-loss levels, and risk management guidelines.
Watch out for
Slack notifications may fail if the webhook URL is incorrect or expires so add error handling that logs failed sends to a dedicated error sheet for manual review.
Tools that fit
OpenAI API LLM Generating structured trade thesis and reasoning
HTTP Request API Ingesting MCP market context data
The agent brief
Everything your agent needs, including the gotchas. Copy it and go.
You are helping me build the following AI agent workflow. ## Goal Short-Term Trade Idea Generation: Ingests market data via MCP to generate structured short-term trade ideas with confidence scores and execution notes. ## Specification - What it does: You get clean, structured short-term trade ideas complete with confidence scores and execution notes, automatically generated from real-time market data to help you spot momentum and catalysts quickly. The process filters out low-conviction setups so your downstream automation systems receive only high-quality JSON-ready insights for immediate action. - Trigger: Triggered by an event (Manual · on demand) - Autonomy: Fully hands-off - Expected setup effort: a few focused days - Tools/services involved: - n8n: Workflow orchestration and AI node execution - OpenAI API: Generating structured trade thesis and reasoning - HTTP Request: Ingesting MCP market context data - Google Sheets: Storing and normalizing asset data - Slack: Notifying users of new trade ideas ## Known pitfalls, handle each one explicitly in your implementation 1. Slack notifications may fail if the webhook URL is incorrect or expires so add error handling that logs failed sends to a dedicated error sheet for manual review. ## Reference implementation https://n8n.io/workflows/12478 (workflow template) Fetch and inspect this before building. If it matches my stack, adapt it; if not, rebuild the pattern with my tools. ## Process requirements 1. Before building: ask me which of the listed tools I actually use and what my platform is (n8n / Make / code / other). Do not assume. 2. Adapt the pattern to my answers; do not force the reference stack. 3. Address every pitfall above; tell me how you handled each. 4. Provide a test plan I can run before letting this touch real data. 5. Ask before any step that sends messages, modifies data, or spends money. Source: https://usecasesforagents.com/use-case/automate-short-term-trade-idea-generation/ via usecasesforagents.com
Frequently asked questions
Can I use a different Automation Platform than n8n?
Yes. n8n is only the example automation platform in this recipe. The same flow works with Home Assistant. Swap the automation platform connection and keep the rest of the setup as written.
Want this running in your business?
This is what I do. I design and build AI agents like this one, and keep them running. If you want it set up for your team instead of doing it yourself, get in touch.
Who it's for
Built for data analysts who want the pull-and-summarize grind automated.