Connecting an AI trading agent to TradingView alerts without losing signals
Disclosure: I work on HookWatch , a hosted TradingView webhook reliability layer. Everything below works without it, and the code is MIT on GitHub. A lot of people are wiring LLM agents to TradingView right now: an alert fires, the agent looks at the signal plus context (position, news, PnL), decides, and places an order. The first version usually looks like this: @app.post ( " /webhook " ) async…
When connecting an AI trading agent to TradingView alerts, losing signals can occur due to the time limit imposed by TradingView. If the receiving server takes longer than three seconds to respond, the request is cancelled. Additionally, TradingView only accepts HTTP ports 80 and 443, without IPv6 support or custom headers, and expects the body to be text/plain or valid JSON.
To prevent signal loss, split the webhook handler from the agent. The handler should perform essential tasks, such as verifying a secret in the JSON body, deduplicating alerts using a unique alert_id, timestamping and enqueuing the signal, and returning a 200 status within milliseconds. The agent can then run in a separate consumer, processing signals from the queue.
After the agent proposes a decision, enforce a risk gate by checking for maximum signal age, position limits, and size limits. Parse the agent's response into a fixed schema to ensure proper handling.
To address potential downtime issues, separate the ingress layer from the agent. Use a fast ACK to handle the 3-second limit, and have the ingress layer write alerts to a durable queue (e.g., Redis Streams, SQS, or a Postgres durable dedupe) for reliable delivery. Set up a dead-letter queue to monitor any signals that keep failing, allowing you to identify and address any missed alerts.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
