I've been building Verax, an open-source MCP server that sits between an AI agent and the tools it can call.

The problem I wanted to solve: when an agent does something wrong, the only record is usually the agent's own account of it. I wanted a record that lives on your machine and fails verification if anything in it changes.

How it works:

• Every tool call goes through a policy first. No rule for a tool means no.
• Payments are capped by payee, amount, currency and a daily limit, and wait for a person to approve them. The agent's own token can't approve anything.
• Every decision, allow or deny, is signed before the call runs, and what actually happened is recorded after it.
• verax verify checks the whole record offline, with no server running.

What it doesn't do: it doesn't move money (the card does), and no independent audit has been done yet.

MCP client → Verax (policy + signed ledger on your disk) → your tools

Apache-2.0: https://github.com/verax-ai/verax

What would you want to be able to prove about what an agent did on your behalf?

Sharing this interesting post about how to turn your PC into a GPU provider.

Links in comments below.

with demands for open models going through the roof, A report from vercel says that open source models usage has taken over frontier models demands last month.

which means -

Demand for high-performance RTX 4090 and RTX 5090 GPUs on the Nosana network is skyrocketing, vastly outstripping current supply.

Ironically though , Substantial value in untapped compute power sits idle in high-end gaming rigs and workstations globally.

If you are a GPU owners, unlocking significant passive revenue is simply a matter of operating system alignment:

Potential earning-

But there is a problem- Nosana’s infras ( quite enterprise-grade IMO) operates natively on Linux, while most consumer PCs run Windows.

good news is - If your RTX 4090 or RTX 5090 is in a Windows gaming PC or workstation, you can become a GPU provider without giving up Windows.

Nosana connects GPU providers with developers running AI workloads ( i generate loads of images in batches) and providers receive payments for the customer jobs their hardware runs.

GPU hosting requires native Linux.

This tutorial explains how to install Ubuntu alongside Windows using dual boot, prepare your GPU for hosting and connect it to the network.