fetch still has to work out, on its own, whether fetch is even the right call for this page, how to start a real project instead of a one-off snippet, how to script something that runs the same way every time, and how to tell whether a change quietly broke something. The Agent Toolkit is the part of the Zenrows CLI that answers those questions directly, so an agent (or the developer directing one) doesn’t have to reconstruct them from scratch on every project.
Each piece solves one specific part of that problem:
init --all sets up a full workspace: every skill, template, workflow, recipe, and eval, plus MCP configured for your agent clients, in one command. plugin install <client> is the narrower path when you only need an agent client wired up: it configures MCP for that client and installs every skill, nothing else. Check what’s already in place at any point with zenrows status.
The Shape of the Problem
fetch, extract, batch, and browser entirely on its own, no agent client, no MCP:
- Connect an MCP-native agent client, Claude Desktop, Cursor, and similar, so the model can discover and call tools directly instead of a human typing CLI commands. MCP sets this up. Only relevant if you’re wiring in that kind of client, an agent that already runs shell commands (like one driving the CLI directly) doesn’t need it at all.
- Decide which primitive fits the task, without guessing. Skills are short, agent-readable playbooks, a master decision tree plus one playbook per primitive, so an agent picks
fetch,extract,batch, or a browser session correctly, without extra prompting from you. - Start a real project instead of an empty file. Templates scaffold a minimal, working project for a specific job, like calling Fetch from Node.js or building a Batch job spec.
- Automate something that has to run the same way every time. Workflows chain multiple Zenrows commands into one named, repeatable process, like keeping a competitor’s pricing data fresh on a schedule.
- Verify that a single command actually works, right now, against a known-good target. Recipes are small, runnable examples that double as a smoke test before you build anything on top of them.
- Benchmark that it keeps working. Evals run the same check reproducibly and write a scored report, so a regression shows up as a failed eval instead of a silent surprise in production.
The Pieces
Every piece follows the same shape:
list to see what’s available, install (or create, for templates) to bring it into your project, explain to read its full docs, and run (for workflows, recipes, and evals) to actually execute it. Learn one, and you already know the other five.
Next Steps
MCP
Connect Claude Code, Cursor, and other clients.
Skills
See the full catalog of agent playbooks.
Templates
Scaffold a working project.
Workflows
Automate a multi-step process.
Recipes
Run one example end to end.
Evals
Benchmark a command with a written report.