u/alpacahq

Hey everyone,

Where can AI fit into a trading workflow?

Generating a useful signal with AI can be one part of the research process, but building an AI-assisted trading workflow involves more than a prompt. It requires thoughtfully a system that treats AI as a research assistant and utilizes how LLMs work underneath.

Carlos Velasco, an Alpaca community member, recently wrote a project he built called Lumiq. According to Carlos, the project uses AI as part of a workflow that includes:

✅ Research: Organizing information and translating trading hypotheses into measureable rules.
✅ Testing and APIs: Connecting with Alpaca’s APIs as part of a workflow involving backtesting, hypothesis validation, and paper trading.
✅ Monitoring: Using a natural-language interface to query information such as open positions, alert triggers, and strategy status. 

Read the full blog: https://alpaca.markets/learn/how-i-use-ai-to-research-and-test-trading-ideas-with-alpaca 

Carlos’s project is one example of how a community member is experimenting with AI alongside trading infrastructure. 

If you’d like to share what you’ve built with Alpaca, we’d love to hear from you! DM us here, share in the Subreddit, or tag us in a post on LinkedIn or X (u/AlpacaHQ).

Curious to learn more about agentic trading with Alpaca? Check out some additional resources below:

• Alpaca’s Skills Library for AI Agents
• Building AI Trading Applications with Alpaca
• Alpaca’s MCP Server
• Alpaca’s Command-Line Interface
• Blogs on agentic trading

 

The Alpaca Team

Disclosure: Alpaca's Disclosure Library (https://alpaca.markets/disclosures) for additional information and disclosures.

Alpaca’s Trading MCP Server now includes read-only access to Alpaca’s API documentation.

A connected assistant can search for  API operations relevant to  a specific task and inspect their parameters, request shape, response fields, constraints, and source documentation.

The new tools cover Alpaca’s Trading API, Market Data API, and authentication references.

With this update, you can:
🔎 Find relevant operations for a specific task
🛠️ Review request fields, supported values, and constraints
📋 Inspect response fields and returned information
🔐 Review authentication requirements for an API workflow

Example prompts include:

• “Which operation should I use to replace an existing order, and what parameters does it require?”
• “What fields are returned when I retrieve my open positions?”
• “Which authentication requirements apply to a paper-trading integration?”
• Learn more about the update
• Review the Trading MCP Server documentation
• Explore the GitHub repository

The documentation tools are read-only and cannot change accounts or order states.

Learn more about Alpaca's MCP Server for Trading API ➡️ https://alpaca.markets/blog/alpacas-mcp-server-for-trading-api-adds-documentation-access

Review the setup documentation ➡️https://docs.alpaca.markets/us/docs/alpaca-mcp-server?ref=alpaca.markets

Explore the GitHub repository ➡️https://github.com/alpacahq/alpaca-mcp-server?ref=alpaca.markets 

Disclosure: Alpaca’s Disclosure Library (https://alpaca.markets/disclosures) for additional information and disclosures.

Hey everyone,

AI is changing how people interact with financial markets, and we’re excited to see Alpaca featured in Bloomberg’s recent article on the rise of AI-powered retail trading.

What was once largely limited to developers is now becoming accessible to a much broader group of traders. Natural-language interfaces and AI-assisted tools are making it easier to build trading workflows and interact with APIs, helping users translate trading ideas and logic into executable trading workflows without building everything from scratch. We’re seeing that shift firsthand in the growth of API-driven trading on Alpaca.

But easier access does not remove the fundamentals of building a reliable trading system: high-quality data, rigorous testing, risk controls, ongoing monitoring, and human oversight.

At Alpaca, we’ve been building the infrastructure and tooling to make agentic trading streamlined, including our MCP Server, CLI, Skills Library, and new and improved SDKs. These tools give builders and AI systems more direct and efficient access to financial markets, helping reduce the friction between expressing a strategy and executing it.

We believe the future of finance will be agent-first, and we’re excited to support this movement by giving AI agents, and the humans behind them, the reliable, real-world access they need to turn new ideas and experimentation into financial products built on reliable infrastructure with appropriate controls.

We provide documentation, setup guides, authentication details, SDKs, example projects, and information on operational and risk considerations to help developers build trading applications responsibly.

Bloomberg article: https://www.bloomberg.com/news/features/2026-08-02/ai-powered-trading-bots-help-retail-investors-take-on-hedge-funds

Resources:

• MCP Server: https://alpaca.markets/mcp-server 
• Trading CLI: https://github.com/alpacahq/cli 
• Skills Library: https://alpaca.markets/blog/alpaca-launches-skills-library-for-ai-agents
• Building AI trading apps: https://alpaca.markets/blog/building-ai-trading-applications-with-alpaca
• New SDKs: https://alpaca.markets/blog/alpaca-rebuilds-its-node-js-sdk-with-broader-api-coverage-and-launches-its-first-supported-java-sdk/

If you’re building agentic workflows with Alpaca, we’d love to hear how you’re structuring research workflows, paper trading, and live guardrails. Drop a comment or post in this Subreddit or tag us on LinkedIn / X (@AlpacaHQ).

Disclosure: Alpaca’s Disclosure Library for additional information and disclosures: https://alpaca.markets/disclosures

Hey everyone,

We’ve rebuilt our Node.js SDK and launched a new Java SDK.

Node.js 4.x is a breaking TypeScript rewrite with broader typed access across Alpaca’s Trading and Market Data APIs. Java 0.1.3 introduces supported clients for Trading, Market Data, and Broker on Java 17 and later.

With this update:
✅ Access expanded Node.js coverage across option-contract reference data, corporate action data, crypto funding, locates, tokenization workflows, and account-activity event streams
✅ Build Java applications across Trading, Market Data, and Broker

Node.js 4.x is not backward compatible with 3.x and requires Node.js 20 or later. Java 0.1.3 requires Java 17 or later.

Learn more below:
● SDK launch blog: https://alpaca.markets/blog/alpaca-rebuilds-its-node-js-sdk-with-broader-api-coverage-and-launches-its-first-supported-java-sdk/
● Node.js SDK: https://github.com/alpacahq/alpaca-trade-api-js● Java SDK: https://github.com/alpacahq/alpaca-java

Disclosure: Alpaca’s Disclosure Library for additional information and disclosures: https://alpaca.markets/disclosures

Hey everyone,

We’ve added index options to the Trading API in paper trading (with live trading coming soon)! 🎉

With Alpaca’s index options in paper, you can:
✅ Test strategies on SPX, SPXW, VIX, VIXW, DJX, and XSP, with more coming soon.
✅ Test cash-settlement flows without share delivery at expiration.
✅ Build and test expiry logic without early-assignment paths.

Want to test index strategies before going live? Details in the comments below.

Read how index options work on Alpaca ➡️ https://alpaca.markets/blog/alpaca-introduces-index-options-paper-trading?utm_source=reddit&utm_medium=social&utm_campaign=alpaca_index_options

How to trade index options with Alpaca: https://alpaca.markets/learn/how-to-trade-options-with-alpaca 

Disclosure: Alpaca's Disclosure Library (https://alpaca.markets/disclosures) for additional information and disclosures.

Hey everyone!

AI trading is moving beyond the "chat bot" phase.

The biggest bottleneck is the gap between spotting a market signal and executing a trade. Achieving this requires an architecture that bridges research, risk, and execution.

We’re seeing this with Agent M, a multi-agent trading platform built by our community. It’s an example of what happens when you combine AI with user-first infrastructure:
✅ Context-Aware Decisions: Generate structured, analytical insights before a single order is placed.
✅ Automated Risk Management: Implements rules-based filtering and custom thresholds to ensure trades align with specific risk profiles.
✅ API-Based Trade Execution: Routes trades directly via Alpaca’s Trading API, closing the loop from signal to market.

As agentic trading grows, we’re excited to see how builders like the Agent M team (Joshua Ang, Shawn Ng, Bryan Chua, Derrick Lim, Jia Yen Beh, and Zi You Foo) design systems that connect AI-assisted research, controlled workflows, and market infrastructure.

Read the full article here: https://alpaca.markets/learn/agent-m-an-autonomous-multi-agent-trading-platform-using-alpaca

If you’d like to share what you’ve built with Alpaca, we’d love to hear from you! DM us or tag us in a post.

Curious about agentic trading with Alpaca? Check out some additional resources below:

• Alpaca’s Skills Library for AI Agents
• Building AI Trading Applications with Alpaca
• Alpaca’s MCP Server
• Alpaca’s Command-Line Interface
• Blogs on agentic trading

Want us to highlight the agentic system you’re building? Post here or tag us on LinkedIn or X (@AlpacaHQ).

Disclosure: Alpaca's Disclosure Library (https://alpaca.markets/disclosures) for additional information and disclosures.

Hi everyone,

We’re starting a new weekly blog series highlighting what our community members are building.

In the first edition, we’re featuring multiple projects across agentic paper trading workflows, portfolio knowledge graphs, product integrations, engineering lessons from automated systems, AI-assisted workflows tested with Alpaca Paper Trading, and an open-source Alpaca MCP library.

Read the full blog: https://alpaca.markets/learn/the-weekly-roundup-1-how-the-alpaca-community-is-turning-ideas-into-ai-trading-workflows

Want us to highlight what you’re building with Alpaca? Post here or our Slack Community, or tag us on LinkedIn or X (@AlpacaHQ).

Disclosure: Alpaca’s Disclosure Library (https://alpaca.markets/disclosures) for additional information and disclosures.

Hi everyone,

Interested in building systematic trading systems that enable you to test ideas faster?

A community member recently shared how he built a system that tests multiple strategies running in paper at the same time. It includes an interactive backtesting dashboard, Alpaca-powered market data and Trading API workflows, and automated monitoring and reporting.

AI helped compress the build cycle, but the builder still owned the strategy logic and risk decisions.

As agentic trading continues to grow, this guide provides an educational walkthrough of how to build an AI-powered testing process in a paper trading environment.

Read the full article: https://alpaca.markets/learn/from-value-investing-to-systematic-trading-building-a-multi-strategy-backtesting-dashboard-with-ai-and-alpaca

Interested in learning more about agentic trading? Check out some additional resources below:

• Alpaca’s Skills Library for AI Agents
• Building AI Trading Applications with Alpaca
• Alpaca’s MCP Server
• Alpaca’s Command-Line Interface
• Blogs on agentic trading

Want to share what agentic systems you’re building? Post here or tag us on our socials.

Insights generated by our CLI, MCP server, and connected AI agents are for educational and informational purposes only and should not be taken as investment advice. Alpaca does not recommend any specific securities or investment strategies. Past performance from models does not guarantee future results. Please conduct your own due diligence before making any decisions. All firms mentioned operate independently and are not liable for one another.

Disclosure: Alpaca's Disclosure Library (https://alpaca.markets/disclosures) for additional information and disclosures.

Hey Trading Herd,

Ready to contribute to your 2026 Individual Retirement Account (IRA)? You can now fund your Alpaca IRA via ACH, and manage distributions via ACH or wire transfer right from your dashboard. 🎉

Available to US tax residents, our IRAs bring the power of algorithmic trading and automation to tax-advantaged account structures.

With our IRAs, you can:
✅ Run your trading bots, scripts, or strategies using API access, similar to a taxable account
✅ Manage both your taxable and retirement portfolios side by side from a single dashboard
✅ Transfer IRA assets in or out with portfolio transfer via ACATS
✅ Fund your IRA via ACH contribution from your dashboard (contribution limits apply)
✅ Trade both US equities and options in your retirement account through the same API

Ready to build your retirement on your terms?

• Open an IRA account
• How to fund your Trading API account
• Portfolio Transfers with Alpaca

Or contact us at support@alpaca.markets.

*IRA accounts are available to all Alpaca Trading API users who are US tax residents with a valid Social Security Number (SSN) or Individual Taxpayer Identification Number (ITIN).

Alpaca's Disclosure Library (https://alpaca.markets/disclosures) for additional information and disclosures

Hi everyone,

A multi-agent trading system including five research agents, one critic agent, a human approval gate, and deterministic risk controls, was recently built by a member of the Alpaca community.

What stood out to us is the architecture pattern. The AI agents help generate structured proposals, but risk controls are handled by deterministic code and every trade proposal goes through human review before execution.

As agentic trading continues to grow, this guide provides an educational walkthrough of one builder's architecture and process in a paper trading environment.

Read the full article: https://alpaca.markets/learn/building-a-multi-agent-ai-trading-system-on-alpaca

Interested in learning more about agentic trading? Check out some additional resources below:

• Alpaca’s Skills Library for AI Agents
• Building AI Trading Applications with Alpaca
• Alpaca’s MCP Server
• Alpaca’s Command-Line Interface
• Blogs on agentic trading

Want to share what agentic systems you’re building? Post here or tag us on LinkedIn or X (@AlpacaHQ).

Insights generated by our CLI, MCP server, and connected AI agents are for educational and informational purposes only and should not be taken as investment advice. Alpaca does not recommend any specific securities or investment strategies. Past performance from models does not guarantee future results. Please conduct your own due diligence before making any decisions. All firms mentioned operate independently and are not liable for one another.

Disclosure: Alpaca's Disclosure Library (https://alpaca.markets/disclosures) for additional information and disclosures. 

Hey everyone,

Alpaca's Postman Collections now stay automatically synchronized with the latest API specifications. 

That means developers have an always up-to-date way to explore, test, and build against the latest API without worrying about stale collections.

This is part of our broader investment to make Alpaca’s API specifications, documentation, and developer tooling the easiest way for builders and their agents to get started.

Explore Alpaca’s Postman Collections: https://www.postman.com/alpacamarkets/alpaca-public-workspace/overview

Disclosure: Alpaca’s Disclosure Library (https://alpaca.markets/disclosures) for additional information and disclosures

Hi everyone,

Hard-to-Borrow (HTB) short-selling is now available through Alpaca's Trading API! 🦙📈

We’re expanding our short-selling capabilities to bring institutional-grade HTB trading directly to your strategies. No more manual broker touchpoints or disconnected locate desks. Build streamlined, programmatic workflows to manage short-selling activity efficiently..

With our HTB workflow, you can:
🚀 Automate the Full Lifecycle: Programmatically get quotes, reserve, and track locate status for HTB securities.
🌙 Access 24/5 Coverage: Respond to market-moving events and earnings releases from Sunday night to Friday night.
📊 Transparent Fees: Short Easy-to-Borrow (ETB) assets with $0 borrow fees, and use built-in controls to manage your HTB locate fees.
🤖 Scale with AI Agents: Build with full support via our Trading MCP Server and CLI for automated, agent-assisted short-selling.

With this workflow, we’re making advanced short-selling as accessible as ETB trading. Check out the docs and tell us what strategies you're building! 🚀

Ready to integrate HTB into your trading systems?

• Read the HTB Trading announcement
• Explore the new HTB and locate documentation
• Set up Alpaca's MCP Server
• Get started with Alpaca's CLI

Questions? Contact our support team at support@alpaca.markets.

Disclosure: Alpaca's Disclosure Library (https://alpaca.markets/disclosures) for additional information and disclosures.

Hey Trading Herd,

Traditional bank wires can take days to hit your brokerage account. With Alpaca’s stablecoin funding, you can use supported stablecoins to access US-listed equities, options, and crypto trading.

Why use stablecoins to fund?
✅ Skip the Bank: Reduce wire fees and waiting for banks to open. Fund your account 24/7, even on weekends.  
✅ Global Access: Stablecoins can simplify cross-boarding funding to access US markets.
✅ All-in-One Trading: Manage your crypto and your stock portfolio through a streamline flow.  

Stop checking to see if the funds are in your account. Use stablecoins to access markets faster and keep your capital moving.

Full announcement: https://alpaca.markets/blog/using-stablecoins-for-securities-and-crypto-trading-with-alpaca/

Disclosure: Alpaca’s Disclosure Library (https://alpaca.markets/disclosures) for additional information and disclosures

Hi everyone,

Big news for all builders: Alpaca is launching the Skills Library for AI Agents! 🦙🤖

We’ve built an open-source collection of reusable skills designed to help AI assistants across Alpaca's API, MCP Server, and CLI.

Our first release, the Trading API Backtesting Skill with CLI, helps agents turn trading ideas into reproducible research workflows with historical simulations, benchmark comparisons, saved results, and clearly documented assumptions.

We're just getting started. Check out the repo and tell us what skill we should build next! 🚀

Ready to try agent-native strategy research?

• Read the Skills Library announcement
• Explore the alpca-skills repository on GitHub  
• Set up Alpaca's MCP Server
• Get started with Alpaca's CLI

  

Questions? Contact support@alpaca.markets.

Disclosure: Alpaca's Disclosure Library (https://alpaca.markets/disclosures) for additional information and disclosures

As the agent-first brokerage infrastructure for financial markets, Alpaca offers many ways to build with us. 

Here's what you can build with:

📈 Trading API for trading systems, applications, dashboards, and custom integrations
🤖 Trading MCP Server for AI assistants such as Claude, Cursor, VS Code, and other MCP-compatible clients
⚡ Trading CLI for terminal-based automation, scripting, and repeatable workflows

To help you get started, Alpaca offers dedicated documentation, including auto-generated API changelogs making it easier to track changes across our platform. 

Read the full announcement ➡️ https://alpaca.markets/blog/building-ai-trading-applications-with-alpaca/
Trading CLI Documentation ➡️https://docs.alpaca.markets/us/docs/alpacas-cliTrading MCP Server Documentation ➡️https://docs.alpaca.markets/us/docs/alpaca-mcp-server

Disclosure: Alpaca's Disclosure Library (https://alpaca.markets/disclosures) for additional information and disclosures

Hey everyone, big news! FINRA's Pattern Day Trader (PDT) rule has been retired and we’ve implemented our new Intraday Margin Framework with.

This is a major regulatory shift that replaces hard restrictions with dynamic, real-time risk management based on actual intraday margin exposure.

Here is what the new rule means for traders:

• No more PDT designation or trade count limits
• The $25,000 minimum equity requirement for day trading is eliminated
• Any current PDT-based account restrictions will be lifted, including the ability to enroll in Alpaca’s High-Yield Cash program

Learn more about how to implement these changes here ➡️ https://alpaca.markets/blog/finra-retires-the-pdt-rule-introducing-alpacas-new-intraday-margin-framework/

Disclosure: Alpaca's Disclosure Library (https://alpaca.markets/disclosures) for additional information and disclosures

Hey Trading Herd,

We've heard from many of you that traditional retirement platforms aren’t designed for active traders.

But that changes today.

We've launched Individual Retirement Accounts (IRAs), available to US tax residents, so you can use your trading expertise and favorite algorithms to manage your retirement portfolio.

By opening an IRA with Alpaca, you can:
✅ Run trading bots and strategies similar to a taxable account
✅ Manage both taxable and retirement portfolios side by side from a single dashboard
✅ Easily transfer your existing IRA accounts with our Portfolio Transfer feature

Ready to build your retirement on your terms? 

Learn more about IRA accounts with Alpaca.

*IRA accounts are available to all Alpaca Trading API users who are US tax residents with a valid Social Security Number (SSN) or Individual Taxpayer Identification Number (ITIN).

Disclosure: Alpaca's Disclosure Library for additional information and disclosures

Hey trading herd, big news! FINRA's Pattern Day Trader (PDT) rule is officially being retired, and we’re implementing the new Intraday Margin Framework on June 4, 2026. 

This is a major regulatory shift that replaces hard restrictions with dynamic, real-time risk management based on actual intraday margin exposure.

Here is what the new rule means for traders:

• No more PDT designation or trade count limits.
• The $25,000 minimum equity requirement for day trading is eliminated.
• Any current PDT-based account restrictions will be lifted.

Learn more about the changes here ➡️ https://alpaca.markets/blog/finra-retires-the-pdt-rule-introducing-alpacas-new-intraday-margin-framework/

Disclosure: Alpaca's Disclosure Library (https://alpaca.markets/disclosures) for additional information and disclosures

Hey Trading Herd,

We just launched a CLI for Alpaca’s Trading API.

Run trades, manage your account, or plug directly into AI agents, all from your terminal.

With Alpaca’s CLI, traders can:
⚡ Go from install to your first paper trade in just 3 commands 
🔐 Use OAuth for paper trading (no API keys or config needed) 
📊 Access 100+ functions across stocks, options, crypto & market data
💻 Automate with JSON output, shell scripts, CI pipelines

Bonus: the CLI is fully generated from our OpenAPI spec, so it stays consistent with Alpaca’s Trading API.

If you’re building trading agents or prefer working in the terminal, this is for you.

• Learn more about the CLI for Trading API
• Get started with Alpaca's CLI

Disclosure: Alpaca's Disclosure Library (https://alpaca.markets/disclosures) for additional information and disclosures