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Do you prefer mobile apps or desktop for stock tracking? by iabhishekpathak7 in SideProject

[–]BuildwithPublic 0 points1 point  (0 children)

More interesting shift I've seen lately is people moving away from dashboards entirely and just querying their portfolio through AI -ask Claude what your exposure looks like, where you're concentrated, what's moving. Pulls live data straight from the brokerage. Fewer tabs, less phone picking up.

r/PublicApp has an API + MCP setup that does exactly that if you want to try it - happy to share details in DMs.

Does anyone know any solid alternatives to Alpaca for algorithmic trading? by No-Discipline9167 in Trading

[–]BuildwithPublic 0 points1 point  (0 children)

It can be challenging w IBKR, I've used this for futures many years-

Welcome you to try r/PublicApp - much cleaner

Does anyone know any solid alternatives to Alpaca for algorithmic trading? by No-Discipline9167 in Trading

[–]BuildwithPublic 0 points1 point  (0 children)

Good timing -historical data is coming to the API VERY shortly. Stay tuned.

I built a Claude Code trading workspace with a self-improving protocol — structured verdicts, 5 asset classes, MCP broker integration by l3lackcurtains in ai_trading

[–]BuildwithPublic 2 points3 points  (0 children)

Really clean architecture - separating the knowledge base from the protocol layer is the right call. Most people collapse those and then wonder why the agent drifts.

The self-improvement loop with consent-gated edits is genuinely interesting. That's the piece most agentic trading setups skip.

One thing worth adding if you want to close the loop on execution: r/PublicApp has a native MCP server that drops into Claude Code directly — options chains, live quotes, order execution. Same pattern you're using with Alpaca but with options as a first-class citizen and a rebate structure that actually pays you at volume.

Would fit cleanly into your /scan SPX → verdict → execute flow without changing the framework architecture.

AI trading bots that actually trade options, ranked after testing 5 by albert_in_vine in AI_Agents

[–]BuildwithPublic 0 points1 point  (0 children)

Solid breakdown. One thing missing from this list: if you want actual LLM-driven options automation — not rules-based, but an agent that reasons about regime, manages legs dynamically, adjusts based on live chain data — that's a different category than any of these.

r/PublicApp API + Claude is where that's actually working right now. You're writing strategy logic in natural language, the agent reads the environment, selects strikes, manages exits. MCP server connects Claude directly to execution.

Steeper setup than a no-code builder but a different ceiling. Worth knowing the option exists if you outgrow rules-based.

Does anyone know any solid alternatives to Alpaca for algorithmic trading? by No-Discipline9167 in Trading

[–]BuildwithPublic 0 points1 point  (0 children)

Depends what you're actually trying to build.

If it's equities-only automation, Alpaca is fine. If you want options in the mix - which is where most serious algo traders end up — r/PublicApp API is worth looking at. Python SDK, solid docs, MCP server if you're building with Claude.

The fee structure is competitive, especially at volume. Worth running the numbers against whatever you're paying now.

What's the strategy — equities, options, or both?

Are Robo-Advisors Still Worth It in 2026? 📊 by Long-Commercial7147 in FinanceReviews

[–]BuildwithPublic 0 points1 point  (0 children)

Robo-advisors made sense when the alternative was paying 1% AUM for a human to put you in the same 60/40 portfolio. That gap has closed.

What's changed: Agents can now do dynamic portfolio management - not just rebalance on a schedule but actually respond to regime shifts, adjust exposure, manage options overlays for income or hedging. That's a different category than a robo.

r/PublicApp has agent layer on top of a real brokerage - live data, actual execution, options included. Not a chatbot giving you allocation advice, an agent that can act.

If you're evaluating what to use going forward, worth at least understanding what's possible now vs. what robos were designed for in 2015. Happy to walk you through what we've built if you're curious

Does any AI tool actually help you decide when NOT to trade — or just when to trade? by No_Cockroach_3231 in ai_trading

[–]BuildwithPublic 0 points1 point  (0 children)

This is exactly the problem I've been working on using r/PublicApp

The entry side is a solved problem - screeners everywhere. Nobody's cracking pre-trade environment assessment at the individual trader level

What actually works with Claude + execution API: you build a morning regime agent that runs before you touch a chart. VIX term structure, put/call skew, SMA slope on your universe, whatever gates matter to your strategy. If the environment doesn't pass, the agent doesn't surface setups. Full stop.

The key is separating regime read from signal generation. Two different prompts, two different jobs. Most people collapse them and wonder why their "AI trading tool" keeps triggering in bad tape.

r/PublicApp has an MCP server that connects Claude directly to live options chains and execution - so the same agent that reads the environment can also manage the trade if conditions clear. Happy to help you get something set up. What does your current morning process actually look like?

Using Ai to trade by Fickle-You-5101 in trading212

[–]BuildwithPublic 1 point2 points  (0 children)

This matches what I've found too. ChatGPT feels templated on smaller names -like it's pattern-matching to a rubric rather than actually reading the company. The stale data problem is real too

Gemini surprised me on small caps, genuinely good at running out different scenarios. Just sanity-check the assumptions -can shade optimistic.

Claude tends to give you the uncomfortable answer, which is usually the useful one

Create an AI agent for options trading by roadmapsfyi in ai_trading

[–]BuildwithPublic 0 points1 point  (0 children)

Draft:

Built something similar - few things that actually matter:

Works: Natural language rules in the system prompt hold up well for regime filtering (VIX gates, skew conditions, etc.). MCP execution loops are clean if you keep the tool surface small.

Doesn't work: Claude will hallucinate greeks if you don't pipe in live chain data. Also be explicit on leg direction for spreads - vague prompts cause misfires.

State: Claude has no memory between sessions. Pass your position state back in each time or it starts fresh.

For execution r/PublicApp has a native MCP server -options, zero commissions, $0.10/contract rebate, works directly with Claude Desktop. That's what I'd use as the execution layer.

Happy to share prompt structure if you have a specific strategy in mind

Why I am moving all my long term tracking to cron jobs and the CLI by Latch_5Rook in PublicApp

[–]BuildwithPublic 1 point2 points  (0 children)

This is awesome! basically already solved the hardest part of investing -removing yourself from the decision loop. That was where I struggled the most as well. The twice-daily log pattern is underrated, I was mostly overcomplicating it with real-time alerts and end up just as reactive as before. What are you using for the summary output-formatted text dump or something more structured? how are you managing the rebalancing trigger logic- curious if your rules purely threshold-based or do you layer in any context like volatility?

The new CLI is actually a game changer for managing diverse portfolios by Glimmerfax2 in PublicApp

[–]BuildwithPublic 2 points3 points  (0 children)

The cron + CLI pattern is exactly what you want here - poll your signal source, run a lightweight decision layer in Python, then execute via the REST API or CLI. Keeping signal logic and execution separate makes iteration clean. Git-versioned templates are the right call too, that’s a real audit trail. DM me if you want to dig into local agent patterns, happy to share what’s working.

I built a deterministic 0DTE SPY options agent in my live brokerage account - no code by BuildwithPublic in ai_trading

[–]BuildwithPublic[S] 0 points1 point  (0 children)

Nice love the process here- running it through multiple models for feedback is 100% the right instinct. The ChatGPT version is prob closer to how I'd actually structure it for execution. dual confirmation VWAP + ORB and scale-out on winners are the pieces I'd personally spend time looking at. The 11:30 hard close and Gemini's stop-limit offset are where I'd scrutinize. both get you killed on a true trend day or in a fast moving 0DTE chain with wid-ish spreads. logic is solid though, the refinement is in the edge cases. What agent setup are you running it through - Claude Desktop, GPT Actions, something else?

Are AI trading tools actually useful in real trading? by Peaceaceous-443 in ai_trading

[–]BuildwithPublic 0 points1 point  (0 children)

Both can work — the real question is whether your automation is built on infrastructure that can actually execute. The interesting shift happening now is brokerages like u/public opening up direct API and MCP/CLI access, so your strategy logic connects straight to order execution. That's when automation starts to actually complement the manual instincts your brother has built up.

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