u/Conscious-Track5313

Hello, I've been building Elvean - native MacOS AI client app that connects to any OpenAI-compatible provider. Recently added a feature I'm pretty excited about:

a full Linux sandbox that AI agents can use to run commands, install packages, and execute code - all inside a lightweight VM on your Mac.

Here is video where AI runs flight-goat-pp-cli — a Go-based CLI for flight ticket searching

from sandbox after installing it directly from github.

How it works:

- Uses Apple's new Containerization framework (open source, shipped with macOS 26) — spins up an Alpine Linux VM in ~6 seconds

- The LLM gets a run_command tool — it can install dependencies, run scripts, compile code, whatever it needs

- There's also a real interactive terminal (SwiftTerm + PTY) so you can jump in alongside the AI — Ctrl+C, vim, top, all work

- Container state persists between sessions — packages you install survive restarts

- The project's workspace folder is mounted at /workspace, so the AI and terminal share the same files

- Total overhead: ~37MB RAM for the sandbox service + ~540MB for the VM process

Curious if anyone else is doing something similar with local sandboxed execution for agents. Most solutions I've seen use Docker or remote VMs - this runs entirely on-device with no dependencies.

I've been working on connecting financial data sources through MCP,
I connected Yahoo Finance MCP + EODHD MCP to a native Mac app I'm building. The model pulls earnings data, renders interactive tradingview + other popular forms of charts, builds sortable tables — all in one conversation.

Added SEC EDGAR as a built-in tool so it can query 10-K/10-Q filings directly. Combined with web search and yahoo-finance-mcp it handles most of what I used to do across 6 browser tabs by running multi-step agentic loop.

The part I'm most excited about: a Knowledge Base that auto-distills key findings from each conversation into an Obsidian style folder with .md files. So when I come back to research the same company later, the model already has context from my previous work.

Full walkthrough with screenshots: https://elvean.app/blog/ai-equity-research-mac/

MCP servers used:

- yahoo-finance-mcp (local, STDIO)

- EODHD (remote, OAuth)

- Financial Datasets (remote, OAuth)

For UI I'm using TradingView and Charts.js

Curious if anyone else is building with MCP for financial workflows — the combination of structured data + rich rendering + agentic chaining feels like it unlocks a lot.

Been working on connecting financial data sources through MCP,
I connected Yahoo Finance MCP + EODHD MCP to a native Mac app I'm building. The model pulls earnings data, renders interactive tradingview + other popular forms of charts, builds sortable tables — all in one conversation.

Added SEC EDGAR as a built-in tool so it can query 10-K/10-Q filings directly. Combined with web search and yahoo-finance-mcp it handles most of what I used to do across 6 browser tabs by running multi-step agentic loop.

The part I'm most excited about: a Knowledge Base that auto-distills key findings from each conversation into an Obsidian style folder with .md files. So when I come back to research the same company later, the model already has context from my previous work.

Full walkthrough with screenshots: https://elvean.app/blog/ai-equity-research-mac/

MCP servers used:

- yahoo-finance-mcp (local, STDIO)

- EODHD (remote, OAuth)

- Financial Datasets (remote, OAuth)

For UI I'm using TradingView and Charts.js

Curious if anyone else is building with MCP for financial workflows — the combination of structured data + rich rendering + agentic chaining feels like it unlocks a lot.

I connected Yahoo Finance MCP + EODHD MCP (77 tools, OAuth) to a native Mac app I'm building. The model pulls earnings data, renders interactive tradingview + other popular forms of charts, builds sortable tables — all in one conversation.

Added SEC EDGAR as a built-in tool so it can query 10-K/10-Q filings directly. Combined with web search and yahoo-finance-mcp it handles most of what I used to do across 6 browser tabs by running multi-step agentic loop.

The part I'm most excited about: a Knowledge Base that auto-distills key findings from each conversation into an Obsidian style folder with .md files. So when I come back to research the same company later, the model already has context from my previous work.

Full walkthrough with screenshots: https://elvean.app/blog/ai-equity-research-mac/

MCP servers used:

- yahoo-finance-mcp (local, STDIO)

- EODHD (remote, OAuth)

- Financial Datasets (remote, OAuth)

I connected Yahoo Finance MCP + EODHD MCP (77 tools, OAuth) to a native Mac app I'm building. The model pulls earnings data, renders tradingview charts, and builds sortable tables — all in one conversation.

Added SEC EDGAR as a built-in tool so it can query 10-K/10-Q filings directly. Combined with web search and yahoo-finance-mcp it handles most of what I used to do across 6 browser tabs.

The part I'm most excited about: a Knowledge Base that auto-distills key findings from each conversation into an Obsidian style folder with .md files. So when I come back to research the same company later, the model already has context from my previous work.

Full walkthrough with screenshots: https://elvean.app/blog/ai-equity-research-mac/

MCP servers used:

- yahoo-finance-mcp (local, STDIO)

- EODHD (remote, OAuth)

- Financial Datasets (remote, OAuth)

I connected Yahoo Finance MCP + EODHD MCP (77 tools, OAuth) to a native Mac app I'm building. The model pulls earnings data, renders candlestick charts, and builds sortable tables — all in one conversation.

Added SEC EDGAR as a built-in tool so it can query 10-K/10-Q filings directly. Combined with web search, it handles most of what I used to do across 6 browser tabs.

The part I'm most excited about: a Knowledge Base that auto-distills key findings from each conversation into an Obsidian style folder with .md files. So when I come back to research the same company later, the model already has context from my previous work.

Full walkthrough with screenshots: https://elvean.app/blog/ai-equity-research-mac/

MCP servers used:

- yahoo-finance-mcp (local, STDIO)

- EODHD (remote, OAuth)

- Financial Datasets (remote, OAuth)

https://testflight.apple.com/join/NtbH4T5R
Elvean - is Private AI wokrspace for Mac with agentic tools, elegant UI, interactive charts, maps, weather cards, sortable tables, Slack-like threads and access to local and cloud models. Runs local models as well as BYOK clouds models from providers like OpenRouter or Ollama.

Seems like the hype is trending down, reminds me the clubhouse. Peter showed the masterclass on how to cash out at the top.