Forem: Cless

Give your AI agent a wallet in under 5 mins with Aethergent

Cless — Fri, 24 Apr 2026 13:37:47 +0000

Building an autonomous agent is one thing; giving it the ability to pay for its own API credits or interact with on-chain protocols is another. Traditionally, this required complex SDKs and API keys.

With Aethergent, you can bypass the onboarding friction and give your agent a wallet with a single HTTP call.

1. The Basics: Crypto, Wallets, and Keypairs

Before we code, let's break down what your agent actually needs to interact with a blockchain like Ethereum:

What is a "Wallet"? In the context of an AI agent, a wallet isn't an app or a physical object. It is a digital identity that allows the agent to sign transactions and hold assets.
The Keypair: Every wallet consists of two mathematically linked strings of characters:
- Private Key: A secret 256-bit number that acts like a digital signature. If your agent has this key, it can move funds. Never share this.
- Public Address: Derived from the public key, this is the "account number" (e.g., 0x742...) that others use to send funds to your agent.
Ethereum/EVM: Ethereum is the network, and the EVM (Ethereum Virtual Machine) is the standard it uses. A wallet generated via Aethergent works across all EVM-compatible chains, including Base, Optimism, Arbitrum, and Polygon.

2. How Aethergent Works

Aethergent is an open API that performs the math required to generate these keys and returns them instantly over HTTPS. It is stateless and zero-auth, meaning no signups or API keys are required.

⚠️ Security Note: Aethergent does not log or store private keys. However, because the key is generated on a server, it is best suited for micropayment wallets and agent operations rather than storing large amounts of capital.

3. Step-by-Step Integration

Step A: Generate the Wallet

Your agent simply needs to make a POST request to the Aethergent root URL.

Using CURL

curl -X POST https://aethergent.com/

Using Python

import requests

# One call to get a fresh Ethereum keypair
response = requests.post("https://aethergent.com/")
wallet = response.json()

print(f"Address: {wallet['address']}")
print(f"Private Key: {wallet['private_key']}")

Using Node.js

const res = await fetch("https://aethergent.com/", { method: "POST" });
const wallet = await res.json();

console.log(`Agent Address: ${wallet.address}`);

Step B: Fund the Agent

Once you have the address, send a small amount of ETH or USDC to it from your own wallet.

Step C: Secure the Key

Do not hardcode the private key. For agents, we recommend:

Environment Variables: Best for Docker or Cloud deployments.
Secret Managers: Use AWS Secrets Manager, GitHub Secrets, or equivalent to keep the key encrypted at rest.
Ephemeral Use: Generate a new wallet for every session if the task is one-off.

4. Advanced: Model Context Protocol (MCP)

If you are using frameworks like Claude Code or Cursor, Aethergent supports MCP.

Your agent can natively discover the generate_wallet tool via a JSON-RPC 2.0 call to /mcp, allowing it to create its own wallet without you writing any custom HTTP logic.

Your agent is now ready to transact on the open web!

What will you build next? Let me know in the comments! 👇

Google Antigravity - Increase font size for the agent chat area

Cless — Thu, 23 Apr 2026 10:06:14 +0000

Google Antigravity is a good IDE for AI-assisted coding. From the release, there has been no option to increase the font size in the agent chat, so it's a pain to read text there.

This Python script will enable setting the font size.

Before

After

It implemented steps described here.

Advent of Agents - Day 8

Cless — Fri, 26 Dec 2025 04:35:29 +0000

More details

Advent of Agents - Day 4

Cless — Mon, 08 Dec 2025 07:18:32 +0000

Agent Engine supports source-based deployment. Your source code deploys directly to production.

Get started with Agent Starter Pack:

For a new project:

uvx agent-starter-pack create my-agent -a adk_base -d agent_engine

Already have an ADK agent? Use enhance:

uvx agent-starter-pack enhance --d agent_engine

Then trigger the deployment with

make deploy

Advent of Agents - Day 3

Cless — Thu, 04 Dec 2025 09:00:15 +0000

Build a powerful AI Agent using Gemini 3 and ADK with native support for Google Search grounding, computer use, and real-time streaming.

1. Setup the project

One liner with Agent Starter Pack

uvx agent-starter-pack create -y --api-key <YOUR_GEMINI_API_KEY> my_agent

Using ADK CLI

uv init
uv add google-adk
uv add google-genai
export GOOGLE_API_KEY="YOUR_API_KEY"
source .venv/bin/activate
adk create my_agent

2. Download sample and run locally

curl 'https://raw.githubusercontent.com/GoogleCloudPlatform/devrel-demos/refs/heads/main/ai-ml/agent-labs/gemini-3-pro-agent-demo/my_agent/agent.py' > my_agent/agent.py
adk web

Advent of Agents - Day 2

Cless — Wed, 03 Dec 2025 01:35:35 +0000

4 lines of text = 1 working AI agent.
No coding. Just YAML.
A working AI agent powered by Gemini 3
Google Search integration

uvx --from google-adk adk create --type=config my_agent
uvx --from google-adk adk web

Advent of Agents - Day 1

Cless — Tue, 02 Dec 2025 13:31:47 +0000

Introduction to Agents

More info here

Story of Esperanto

Cless — Sat, 29 Nov 2025 14:23:04 +0000

I'm learning Esperanto, lingvo de paco - the language of peace. Here are interesting things about its history.

Google ADK Tutorials

Cless — Sun, 23 Nov 2025 12:12:16 +0000

I'm putting a list of tutorials for Google ADK (Agent Development Kit). This is the foundation.

A quick start to get a feel of Google ADK
Foundational concepts
First experience with ADK tools
A good crash course
ADK pattern with Memory and MCP (Model Context Protocol)
google/adk-samples: A collection of sample agents built with Agent Development (ADK)
Study Note « AI Agent from Annie Wang

Setup Gstreamer with Python on Windows

Cless — Wed, 19 Nov 2025 04:44:49 +0000

When I started trying GStreamer with Python on Windows 10, it took me quite some time to set up the development environment. So this might help others on the way.

The most convenient approach is through MSYS2. Here are the steps:

1. Download and install MSYS2: https://www.msys2.org. Remember [msys2_path] for environment variable.

2. Install Python, GStreamer, tools, plugins, and PyGObject

Open MSYS2 UCRT64 terminal
Update MSYS2 pacman -Syu. After this, the terminal may close; you need to open it again.
Install gcc pacman -S mingw-w64-ucrt-x86_64-gcc
Install Python, GStreamer, tools, plugins, and PyGObject pacman -S mingw-w64-x86_64-python3 mingw-w64-x86_64-gstreamer mingw-w64-x86_64-gst-devtools mingw-w64-x86_64-gst-plugins-{base,good,bad,ugly} mingw-w64-x86_64-python3-gobject

Add the following paths to ~/.bashrc

export PATH="<msys2_path>/mingw64/bin:$PATH"
export XDG_DATA_DIRS="<msys2_path>/mingw64/share/:$XDG_DATA_DIRS"

Apply bashrc: source ~/.bashrc

3. Test: run this on the terminal

pip install pygobject
python -c "import gi; gi.require_version('Gst', '1.0'); from gi.repository import Gst; print(Gst.version_string())"