31 tools· updated sep 2026

CURATED BY AN OPERATOR, NOT A CRAWLER

The short list of AI agent tools that actually work.

Every tool here ran inside a real production workflow first. 31 made the list. The other two hundred did not. Verdicts from daily use, re-checked monthly.

No sponsored placements. No scraped lists.

GAT: Gather, Assess, Trigger. A black pawn casts the shadows of a rook, bishop, queen, knight and king.
31tools tested
12running daily in production
9categories
0sponsored placements

FEATURED

Picks from the list

Twelve tools carrying real workflows right now. Each entry says what it is good at and when to skip it, and each one links to a full review.

Agentic coding and ops in the terminal.

Runs my daily operations: reports, deploys, file work, whole pipelines. The tool I measure every other agent against.
BEST FOR
real work in real repos, end to end
SKIP IF
you want a chat window, not a worker

# coding-agents

One protocol to wire agents into your tools.

Design files, analytics, email, hosting. One standard instead of custom glue per app. This is where agent stacks are heading.
BEST FOR
connecting agents to an existing stack
SKIP IF
you automate a single app

# mcp-servers

Playwright

RUNNING

Browser control agents can rely on.

Logins, scraping, UI checks. Handles real-world pages and auth better than anything else I put into rotation.
BEST FOR
web automation behind a login
SKIP IF
plain HTTP gets the data

# browser-automation

The production stack behind my SEO agent.

Claude Code, Ahrefs, Search Console, Playwright and a custom agent. Each tool has one job, a human approves what ships.
BEST FOR
running SEO as an agent workflow
SKIP IF
you publish twice a year

# custom-agents

Paid social under full agent control.

Full scope: campaigns, ad sets, creatives, audiences, budgets and reporting. Agents run the ops, a human signs off on spend.
BEST FOR
automating Meta campaigns end to end
SKIP IF
you run one campaign and edit it by hand

# ad-platforms

Search campaigns without the console grind.

Full scope: campaigns, keywords, bids, budgets and reports. Same rule as Meta, agents operate, humans approve spend.
BEST FOR
search ops at scale
SKIP IF
spend is too small to automate

# ad-platforms

Make

RUNNING

No-code glue that keeps running for months.

Lead forms to sheets, webhooks to CRMs. Scenarios I built once and stopped thinking about.
BEST FOR
wiring SaaS apps without code
SKIP IF
the logic fits in thirty lines of code

# orchestration

n8n

RUNNING

Visual workflows with an agent layer on top.

The AI nodes matured enough to carry production pipelines. Visual ops the whole team can read.
BEST FOR
teams that want visual ops
SKIP IF
your team prefers code-first

# orchestration

Real search queries and positions, from the source.

Every content decision on this site starts from it: real queries, real positions, and whether Google indexed the page at all. Estimates describe the market; this describes my pages.
BEST FOR
planning content from measured demand
SKIP IF
the site you care about is not yours

# data-scraping

Figma MCP

RUNNING

Design files agents can read, not guess.

Entire landing pages went from mockup to deployed code through it. Node ids make prompts precise, tokens survive into the code, and the visual check stays human.
BEST FOR
design-to-code with a real design file
SKIP IF
the project has no design artifact

# mcp-servers

The channel my agents report through.

Background work is invisible until a message says what happened. Daily numbers to a group, failures to my DM, one POST request each, read within minutes.
BEST FOR
closing the loop on every automated job
SKIP IF
your team does not live in Telegram

# monitoring-evals

The table humans and agents co-author.

Agents append rows and fill blanks, people read, filter and correct. Append-only writes plus a dedup key made months of reruns boring, with zero data lost.
BEST FOR
reports non-technical people actually use
SKIP IF
no human ever opens the sheet

# data-scraping

BROWSE

Tools by job

Categories follow what agents do all day, not marketing labels.

Coding agents4

Agents that write, fix and ship code.

MCP servers6

Connectors between agents and your tools.

Memory & context2

What your agent remembers between runs.

Browser automation3

Clicking, scraping and testing the web.

Orchestration4

Multi-step and multi-agent pipelines.

Data & scraping4

Feeding agents clean, current data.

Monitoring & evals3

Knowing when your agent breaks, before users do.

Ad platforms2

Campaigns agents operate, humans approve.

SaaS building3

From idea to shipped product, agents in the loop.

METHOD

How a tool gets on the list

01

Run it

Every candidate goes into a live workflow for at least two weeks. A demo is not evidence.

02

Break it

I note what fails: rate limits, quirks, silent costs, the parts changelogs skip.

03

Verdict

RUNNING, TESTED or WATCHING. Re-checked monthly. Tools get dropped. The list stays short.

BLOG

Latest field notes

Write-ups from daily use: what shipped, what got cut, and what I would not run again.

Read all posts

FOR TEAMS

Your team ships its first agent workflow.

One workshop. No slides about the future of AI. We take one real process from your operations and automate it with the stack from this list.

  • A working agent workflow on your own process
  • Stack decisions made, with reasons written down
  • A playbook your team keeps and extends

Introhalf day · remote

Agent basics plus the stack. Your team leaves knowing what to build first.

Hands-on2 days · remote

We build a working workflow on your real process. You keep it.

Customscoped

Bigger rollout or a specific stack. Tell me the problem first.

CLIENTS

Clients worldwide

Teams we trained and agents we shipped, by location.

9 clients · 8 countries · 5 continents

ABOUT

Who runs this

~/operator $ whoami

Marek. Eight years in performance marketing and automation ops. I run AI agents on real business workflows every day. This site is the list I wish I had when I started.

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