A developer’s guide to settings.json in Claude Code (2025)

If you’re a developer who lives in the command line, Claude Code probably sounds like a dream. An AI coding assistant that works right where you do, promising a native way to weave AI into your daily workflow. But if you’ve actually tried to set it up, you’ve likely run into its biggest hurdle: a configuration system that can feel downright hostile.

The key to unlocking all that power is supposed to be in its settings files, especially "settings.json". The problem is, many developers spend more time fighting with their Claude Code setup than they do fixing bugs in their own code. Between a messy hierarchy of config files and permissions that don’t always stick, it’s easy to get lost.

This guide is here to cut through the noise. We’ll walk through what "settings.json" is supposed to do, make sense of the tangled configuration files, cover the most common issues, and point you toward a much simpler way to build and manage AI agents for your business.

What is settings.json Claude Code?

So, what’s "settings.json" supposed to be?

First, a quick refresher. Claude Code is an AI tool from Anthropic built to help you with coding, debugging, and running tests right from your terminal. The "settings.json" file is meant to be the central control panel for customizing how it behaves.

A screenshot showing the settings.json file for Claude Code, which is the central control panel for customizing the AI's behavior.

This is where you’re supposed to define security permissions, set up environment variables, turn on different tools, and tweak the AI’s workflow. But as many have found out the hard way, it’s just one part of a confusing puzzle of settings files that can override each other in unexpected ways, leading to hours of frustration.

The confusing hierarchy of settings.json Claude Code configuration files

The number one headache for most developers using Claude Code is just trying to figure out which config file to edit. A setting that works one day might mysteriously break the next because it’s being overridden by another file you forgot existed. This isn’t just a small annoyance; it’s a huge time-waster.

Here’s a look at the different settings files and how they’re supposed to interact, going from the most general to the most specific:

• The legacy file ("~/.claude.json"): This is where things start to get weird. While it’s not part of the "official" hierarchy, users report it’s often the only place certain settings actually work. On Reddit, developers describe it as a chaotic grab bag for global settings, project configs, prompt history, and stats. It’s messy, unpredictable, and often the file you turn to when nothing else is working.

• User settings ("~/.claude/settings.json"): These are your personal, global settings that apply to every project. Think of it as the place for your personal defaults, like a preferred theme or a specific model you like to use.

• Project settings (".claude/settings.json"): These settings are tied to a specific project. You’d typically check this file into source control so everyone on the team has the same base configuration for things like running tests or using project-specific tools.

• Local project settings (".claude/settings.local.json"): This is for your personal tweaks within a project. It’s ignored by Git, making it the right spot for API keys or any experimental settings you don’t want to commit for the whole team.

To make it even more complicated, any of these files can be overridden by enterprise policies or command-line arguments. The result is a tangled web of configurations that makes debugging a simple permission issue a real chore.

If this sounds like a lot of file-hopping just to get a setting to stick, you’re right. It is. With a platform like eesel AI, all of this is handled through a clean, self-serve dashboard. Instead of hunting through JSON files, you can connect your knowledge sources, define your AI’s persona, and set detailed permissions with a few clicks. You can be up and running in minutes, not days.

Key configurations in settings.json and common pitfalls

Let’s get into the specific settings that seem to cause the most trouble. This is where the promise of deep customization runs into the reality of a system that can be buggy and unreliable.

Permissions: Allow, ask, deny

In theory, the "permissions" object is your security guard. It lets you decide which tools and commands Claude Code can run on its own ("allow"), which ones need your okay first ("ask"), and which ones are off-limits ("deny"). This is incredibly important for preventing the AI from doing something you’ll regret, like deleting files or reading sensitive data.

A visual representation of the security guardrail in settings.json Claude Code, which controls permissions for tools and commands.

The reality? It just doesn’t always work. There are tons of reports on Stack Overflow and Reddit about "deny" rules being flat-out ignored. A developer might set a rule to block access to their ".env" file, only to watch in horror as Claude reads it anyway. This isn’t just a bug; it’s a security risk that makes it hard to trust the tool.

Tools and integrations: Hooks & MCP

You can extend Claude Code with new skills using hooks (custom shell scripts) and the Model Context Protocol (MCP) for connecting to other services. This sounds great for power users, but it comes with a steep learning curve. Setting up an MCP server isn’t a trivial task, and managing a collection of shell scripts just adds another layer of things to maintain.

An illustration of how hooks can be used in settings.json Claude Code to extend its capabilities with custom scripts.

The real problem here is that the system is both tricky to use and not entirely reliable. You can’t fully trust the permission system to keep your environment safe, and adding new capabilities takes a lot more effort than most busy teams can afford.

Setting	Purpose	Common Pitfall
"permissions"	Control tool and file access for security.	"deny" rules are often ignored, leaving sensitive files exposed.
"hooks"	Run custom scripts before or after tool use.	Requires writing and maintaining separate shell scripts, adding complexity.
"model"	Specify which Claude model to use.	Can be overridden by other settings, leading to surprise costs or performance.
"mcpServers"	Connect to external tools and services.	Complicated to set up and often requires running separate server processes.

This is a classic trade-off: powerful customization that’s also a pain to manage. But what if you could have both? With eesel AI, you can create custom actions for your AI, like looking up order info or updating a customer record, using a guided editor in a simple UI. You can even test your changes in a simulation environment on thousands of your past tickets to see exactly how the AI will behave before it goes live. You get full control and confidence, without the risk.

This video explains the Claude Code permission system and how to configure settings.json with real examples.

The developer experience: Scriptability vs. usability

The idea of a coding assistant that lives in your terminal is really compelling. It promises a workflow that’s fast, scriptable, and tied into the tools you already use every day.

But the experience of using Claude Code often doesn’t live up to that promise. It’s so challenging that the community has had to create its own tools just to manage the config files, like the "ccsettings" helper that showed up on Hacker News. When people have to build tools just to manage your tool, that’s a pretty clear sign something’s not quite right.

This setup is also clearly built for one person, not a team. Sure, you can share the ".claude/settings.json" file in Git, but it’s a clunky way to handle team-wide configurations. There’s no central dashboard to monitor usage, see how it’s performing, or make sure everyone is using the same security rules. It’s a great tool for tinkerers, but it’s not a solution for businesses that need reliable and manageable AI agents.

If you’re running a business, you need a platform designed for teamwork and real-world results. eesel AI gives you clear reporting to help you find gaps in your knowledge base, lets you roll out changes gradually, and pulls knowledge from dozens of sources like Confluence, Google Docs, and past support tickets without anyone ever touching a JSON file. It’s built for business outcomes, not just for developer experiments.

Claude Code pricing

To use Claude Code, you need a paid subscription or API access. The individual plans look like this:

• Pro: $20 per month for everyday use.

• Max: Starts at $100 per month for 5x the usage of the Pro plan, with options to go higher.

One thing to watch out for is that these plans come with usage limits that can change depending on server traffic. This can make the tool’s availability unpredictable, especially if you’re a heavy user. For a business depending on this for something critical like customer support, that kind of variability is a non-starter.

Simplify with predictable pricing

In contrast, eesel AI’s pricing is straightforward and predictable. You pay based on the features and capacity you need, and you’re never charged per resolution. This means your costs won’t suddenly jump after a busy month, which makes budgeting for AI a whole lot easier.

Build reliable AI agents without the settings.json Claude Code headache

Look, Claude Code can be a powerful tool if you’re a solo developer who loves to tinker and has the patience for its quirks. The deep, code-level control it offers is impressive, but it comes at a high price in usability, reliability, and team-readiness. For businesses trying to build AI agents for customer support or internal helpdesks, the engineering effort can quickly cancel out the benefits.

The future of building AI agents isn’t about manually editing "settings.json" files and crossing your fingers. It’s about using intuitive, powerful platforms that manage the complexity for you so you can focus on what matters.

If you’re tired of debugging config files and want to launch powerful, reliable AI agents that learn from all your company knowledge, eesel AI was built for you. Connect your helpdesk, chat tools, and knowledge sources in minutes, and use our powerful simulation engine to launch with confidence. Try eesel AI for free today.