Walnut vs Alpaca: Which Is Better in 2026?

Figures and features are point-in-time and change; treat the table as a starting map, not a live quote.

The AI that knows your portfolio. Ask anything in plain English, research any stock or fund, and get an honest second opinion, on the broker you already use. Read-only by default, you approve every trade, and it never holds your money. Walnut is not an investment adviser.

How it works: You connect the brokerage you already use through a secure, read-only link, so your login stays with your broker and Walnut sees positions rather than credentials. You then analyze and manage that portfolio by talking through Claude or ChatGPT, and you can group holdings into thematic baskets built around a thesis. When you decide to act, Walnut prepares the trades and routes them back to your own broker for you to approve.

In practice, Walnut’s AI conversational + thematic baskets + trade. It falls under chat-driven management of your own brokerage, which makes it best suited to talking to your own brokerage with ai. On connecting an account it is “Yes (your own broker)”, and on execution it is “Read + you approve”. It is priced as free tier.

One honest limitation: It sits on top of your broker rather than being a broker itself, so you connect an existing account.

A developer-first brokerage with an official MCP server for real-time data, paper trading, and execution by AI agents. Best for people who code.

How it works: Alpaca is a brokerage you talk to through code: a REST and websocket API exposes market data, paper trading, and live commission-free execution, and its official MCP server lets an AI agent pull data, test in a paper account, and place real orders programmatically. You build (or wire up an agent against) that API rather than tapping buttons in an app.

In practice, Alpaca’s AI official mcp server (data + execution). It falls under for builders: connect a broker to an ai agent, which makes it best suited to developers building ai agents. On connecting an account it is “Alpaca accounts”, and on execution it is “Read + trade + paper”. It is priced as free (open source).

One honest limitation: Developer-first; requires code and self-hosting.

The honest framing: Alpaca is about developer-level, programmatic control for building your own AI agent, while Walnut is about a no-code experience across most US brokers. Alpaca is built for developers who write code, whereas Walnut is a no-code app that sits on top of your broker.

Every tool gives something up for what it does well. Here is the honest give-and-take on each, so you can weigh the specific strengths against the limitations that come with them rather than judging on the headline category alone.

For AI investing tools, the distinction that matters most is whether the tool works from your actual, connected positions or reasons from something else: a separate account it manages for you, or the tickers and numbers you feed it. It decides how personal the answers can be, and where your money physically lives.

• Walnut: reads your real connected holdings. Walnut connects your real brokerage (Yes (your own broker)) and works from your actual positions, so its answers reflect what you genuinely own rather than a generic model.
• Alpaca: connects specific supported accounts. Alpaca connects a defined set of accounts (Alpaca accounts), so whether it can see your holdings depends on whether your money is at one of them.

This is where they diverge most. One works from your real, connected account while the other does not, so if you want an assistant grounded in the exact positions you already hold, that gap is the thing to weigh first. This holdings-aware angle is the one Walnut is built around: it connects the brokerage you already use and reasons from your live positions, read-only by default, with any trades left for you to approve.

There is no universal winner here; the right pick depends on the job you are hiring the tool for. Match the category to your intent rather than chasing a single “best.”

• Choose Walnut if you want talking to your own brokerage with ai. Its AI conversational + thematic baskets + trade, it is priced as free tier, and it fits chat-driven management of your own brokerage. It is built for hands-on investors who want an AI layer on the broker they already have, without moving their money. Keep in mind that it sits on top of your broker rather than being a broker itself, so you connect an existing account.
• Choose Alpaca if you want developers building ai agents. Its AI official mcp server (data + execution), it is priced as free (open source), and it fits for builders: connect a broker to an ai agent. It is built for developers building their own automated or AI-driven trading systems. Keep in mind that developer-first; requires code and self-hosting.

Because they sit in different categories, this is not strictly either-or: some investors use one for talking to your own brokerage with ai and the other for developers building ai agents, and just watch for overlapping costs.

Cost is easy to misread when two tools charge in different shapes, so compare the model, not just the number. Walnut is priced as free tier, while Alpaca is priced as free (open source). A percentage-of-assets fee scales with your balance, a flat subscription does not, and a “free” tier usually earns elsewhere (on cash, order flow, or premium upgrades), so the cheapest headline is not always the cheapest outcome for your situation.

Pricing and tiers change often. Confirm the current numbers on each provider’s own site before you decide; the framing above is point-in-time.