Setting Up Claude Code with Custom Prompt Templates

Claude Code has quickly become one of the most popular AI coding assistants, and for good reason. It runs directly in your terminal, understands your entire project context, and integrates with your existing development workflow. But most developers are only scratching the surface of what it can do.

In this guide, we'll cover how to set up Claude Code with custom prompt templates for repeatable tasks, and how to integrate Promptster's MCP server so you can test those templates across multiple AI providers -- all from your terminal.

Understanding CLAUDE.md

Every Claude Code project can have a CLAUDE.md file at the root. This file acts as persistent context -- Claude reads it at the start of every conversation and follows the instructions inside. Think of it as a system prompt for your entire project.

A well-structured CLAUDE.md includes:

• Project overview -- what the codebase does, what stack it uses
• Code conventions -- naming patterns, file structure, testing expectations
• Commands -- how to build, test, and deploy
• Key files -- where to find important logic
• Gotchas -- known issues, constraints, things that break easily

Here's a minimal example:

# CLAUDE.md

## Project
React + TypeScript SPA with Express backend. Drizzle ORM, PostgreSQL.

## Commands
- `npm run dev` -- Start dev server
- `npm run test` -- Run tests
- `npm run check` -- TypeScript type checking

## Conventions
- Functional components only
- Use TanStack Query for server state
- All API routes in /api directory

This context makes Claude Code dramatically more effective. Instead of guessing your project structure, it knows where things live and how they should be written.

Creating Reusable Prompt Templates

While CLAUDE.md handles project-wide context, you'll often have repeatable tasks that benefit from standardized prompts. Here are templates we've found effective across many projects.

Code Review Template

Review this code for:
1. Security vulnerabilities (injection, XSS, auth bypass)
2. Performance issues (N+1 queries, unnecessary re-renders, memory leaks)
3. Error handling gaps (missing try/catch, unhandled promise rejections)
4. Naming and readability

For each issue, explain the risk and suggest a specific fix.
Do not comment on style preferences -- only flag objective problems.

API Endpoint Template

Create a new API endpoint with the following specification:
- Method: [GET/POST/PUT/DELETE]
- Path: /api/[path]
- Auth: [required/optional/none]
- Input: [describe the request body or query params]
- Output: [describe the expected response shape]
- Error cases: [list expected error scenarios]

Follow the existing patterns in the /api directory.
Include input validation, error handling, and TypeScript types.

Bug Investigation Template

A user reported: [describe the bug]

Steps to reproduce:
1. [step 1]
2. [step 2]

Investigate the likely cause by:
1. Tracing the relevant code path
2. Identifying where the behavior diverges from expected
3. Suggesting a fix with minimal blast radius

These templates ensure consistency across your team and make it easy to hand off tasks to Claude Code without writing detailed instructions every time.

Adding Promptster's MCP Server

Here's where it gets interesting. Claude Code supports MCP servers, which means you can connect Promptster and test prompts against multiple AI providers directly from your terminal.

Configuration

Add the following to your Claude Code MCP configuration:

{
  "mcpServers": {
    "promptster": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://www.promptster.dev/mcp"],
      "env": {
        "API_KEY": "pk_live_your_key_here"
      }
    }
  }
}

This uses mcp-remote as a bridge to connect Claude Code's stdio-based MCP protocol to Promptster's HTTP-based server. Replace the API key with your own -- you can generate one from Developer > API Keys in Promptster.

Why This Matters

With Promptster connected, Claude Code gains the ability to:

• Test any prompt against multiple providers -- "Test this system prompt on OpenAI, Anthropic, and Google"
• Compare responses side by side -- "Compare how each provider handles this edge case"
• Score response quality -- "Evaluate these responses on relevance and accuracy"
• Access your test history -- "Show me the last 10 tests I ran for this project"

This is particularly powerful when you're building AI-powered features. Instead of guessing which model handles your use case best, you test it directly from the same terminal where you're writing the code.

A Practical Workflow

Let's walk through a real scenario. You're building a content moderation system and need to write a classification prompt.

Step 1: Write your initial prompt in your codebase.

Step 2: Ask Claude Code to test it: "Use Promptster to test this moderation prompt with a set of sample inputs across OpenAI, Anthropic, and Groq. I need fast, accurate classification."

Step 3: Claude Code calls Promptster's MCP tools, runs the comparison, and reports back with response times, quality scores, and costs for each provider.

Step 4: Based on the results, you refine the prompt. Maybe Groq was fastest but missed some edge cases. Maybe Anthropic was most accurate but too slow. You iterate right there in your terminal.

Step 5: Save the final version as a baseline test in Promptster. Set up a scheduled test to run weekly and alert you if quality degrades after model updates.

The entire workflow -- writing, testing, comparing, and monitoring -- happens without leaving your development environment.

Tips for Claude Code Power Users

Keep CLAUDE.md updated. Every time you add a major feature, change a convention, or discover a gotcha, update the file. The more accurate it is, the better Claude Code performs.

Use slash commands. Claude Code supports custom slash commands that map to specific skills. Combine these with your prompt templates for even faster workflows.

Layer your context. CLAUDE.md at the project root handles global context. You can also add context files in subdirectories for module-specific instructions. Claude Code picks up both.

Test prompt changes before deploying. This is the whole point of the Promptster integration. A prompt that works perfectly in development might behave differently in production across providers. Test it across your target models before shipping.

Get Started

If you're using Claude Code without custom prompt templates and MCP tools, you're leaving significant productivity on the table. Set up your CLAUDE.md, create templates for your recurring tasks, and connect Promptster for multi-model testing.

Get your API key and check the full MCP integration docs for detailed setup instructions across all supported clients.