---
title: Claude Code setup guide
category: guide
canonical: https://forgehouse.ai/guides/claude-code-setup/
lang: en
hreflang_alt: https://forgehouse.ai/tr/rehberler/claude-code-kurulum/
last_updated: 2026-06-20
---

# Claude Code setup guide

> Setting up Claude Code gives the model a harness with direct access to your files and tools, which is what turns it from a chat assistant into an operator that does real work.

## What is Claude Code?

Claude running in your terminal with access to your files and tools, not just a chat window. It reads and writes files in a project folder, runs commands, and checks its own output. That file-and-tool access is the whole point, it works inside your project instead of describing what to do from the outside.

The shift is from advice to action. A chat window can only tell you what to type; Claude Code can open the file, make the change, run the test, and read the result, all inside the directory you point it at. It is still the same model doing the reasoning, but now it operates on your actual project rather than on a description of it. That is why "setup" matters at all: the setup is what grants the access, and the access is what makes the work real instead of hypothetical.

## Why does a harness change what the AI can do?

A bare chat writes you advice; a harness turns that into a system that does the job: opens files, edits them, runs the command, and verifies the result. The model is the same, but the harness gives it hands. That is the gap between 'here's how you'd fix it' and the fix actually landing in your code.

Verification is the part people underrate. Because the harness can run the command and read the output, the model can catch its own mistake instead of confidently handing you broken advice. It edits, it runs, it sees the error, it corrects, a loop a chat window simply cannot close because it never touches the running system. That self-checking loop is the difference between a suggestion you have to test by hand and a change that has already proven itself before you look at it.

## What do you need to get started?

Three things: a Claude account, the install, and a project folder to point it at. There's no server to stand up or pipeline to wire first, you open a directory and start working. Everything else, skills and tool connections, layers on once the basics run.

The honest reassurance here is how little ceremony there is. You do not architect anything up front; you open a folder and begin, and the more powerful pieces attach later when you actually need them. Resist the urge to wire up every connector and skill on day one. Get the basic loop working, open a file, ask for a change, watch it land, and add the rest only once that core feels natural. A setup that starts small and grows beats one that stalls trying to configure everything before the first useful task.

## How do skills and MCP fit in?

A skill is a discipline you load, a documented method the model follows for a specific kind of work. MCP is the bridge to real tools: analytics, ad platforms, search, your database. Skills tell it how to think about a job; MCP gives it the live data and actions to do the job instead of guessing.

They cover two different gaps, and most serious work needs both. If the model cannot see your data, that is an MCP gap, a connection problem. If it sees the data but handles it like a generalist instead of a specialist, that is a skill gap, a method problem. An SEO audit, for instance, uses an MCP connection to pull the live Search Console rows and a skill to interpret them the way an expert would. Claude Code is the harness that holds both together: the hands, the method, and the live data in one place.

When you are ready to add the method and data layers, the [catalog](/catalog) lists the skills, agents, and connectors you can plug into a working setup, organised by the job they do. And to understand the two pieces you will lean on most, start with [what are Claude skills](/guides/what-are-claude-skills/) for the method layer and [what is MCP](/guides/what-is-mcp/) for the live-data layer, the two halves that turn a bare install into an operator.

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Maker: Can Davarcı, https://candavarci.com.tr