Context7
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Description from the maker (original English)
Search the Claude Code Ultimate Guide and machine-readable references from any MCP client.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
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Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"claude-code-guide": {
"command": "npx",
"args": [
"-y",
"claude-code-ultimate-guide-mcp"
]
}
}
}Run this in your terminal
claude mcp add claude-code-guide -- npx -y claude-code-ultimate-guide-mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"claude-code-guide": {
"command": "npx",
"args": [
"-y",
"claude-code-ultimate-guide-mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"claude-code-guide": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"claude-code-ultimate-guide-mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
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These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
The registry name was verified with the GitHub account FlorianBruniaux, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (1.3.7) reached the registry 9 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Context7, Codebase Memory, Exa
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
Florian BRUNIAUX · Fractional Chief AI Officer
13 years from developer to CTO / VP Eng · Blog ↗ · Projects ↗
Learn Claude Code, build reliable agents, and scale their use safely. The website is the primary reading and discovery interface. This repository contains the canonical Markdown sources, reusable files, machine-readable indexes, and contribution history.
Start here: complete a first task online · browse the guide portal · open the complete sitemap · read the Markdown source
The table below is generated from machine-readable/navigation.json. The same contract feeds the public sitemap, so the repository and website expose the same intent model.
| Intent | Browse online |
|---|---|
| Start | Guide portal · Quick Start · Learning Paths · Quick Reference · AI Roles |
| Build | Agent Harness Engineering · Loop & Graph Engineering · AI Design Patterns · Context Engineering · Memory Systems · Workflows · Methodologies · MCP or CLI? · Examples |
| Scale | Security · Enterprise Governance · Observability · Team Metrics · Team Adoption · AI FinOps · LLM Market Snapshot · Subscription Strategy · AI Unit Economics · Team Knowledge · API Gateway |
| Resources | Resource Hub · Downloads · Cheat Sheets · Ebooks · Diagrams · Ecosystem · Compare · Glossary · FAQ · Guide MCP Server · Related Projects |
| Updates | Guide Changelog · Claude Code Releases · RSS Feed |
Claude Code documentation explains the product. This guide connects product behavior to engineering decisions: what belongs in context, when to use an agent instead of a skill, how to verify generated work, and which controls matter when usage moves beyond one developer.
| Need | Start with |
|---|---|
| Understand Claude Code internals | Architecture and Tools Reference |
| Design agent systems | Agent Harness Engineering, Loop & Graph Engineering and AI Design Patterns |
| Structure AI-assisted delivery | Methodologies and Workflow Guides |
| Establish a security boundary | Security Hardening and Sandbox Isolation |
| Validate understanding | Knowledge Quiz and Recap Cards |
The guide favors explicit trade-offs and verifiable procedures. Where evidence is incomplete, the relevant page should preserve that limit instead of presenting one workflow as universal.
Anthropic recommends the native installer, which updates itself:
# macOS, Linux, WSL
curl -fsSL https://claude.ai/install.sh | bash
# Windows PowerShell
irm https://claude.ai/install.ps1 | iex
Alternatives that do not auto-update: brew install --cask claude-code, winget install Anthropic.ClaudeCode, or npm install -g @anthropic-ai/claude-code (Node.js 22+). See the official setup page.
Verify the installation and authenticate:
claude --version
claude doctor claude auth login
The Quick Start chapter documents installation alternatives, authentication, updates, permission modes, and common first-day failures.
Open a small repository with a clean or understood Git state, then start Claude Code:
cd your-project
claude
Give Claude a bounded request that includes the expected result and verification:
Explain how this project runs its tests. Do not modify files.
Name the relevant commands and cite the files that define them.
Before asking Claude to edit code, add a project-level CLAUDE.md that records the commands and constraints Claude must follow:
# Project instructions
npm testnpm run lint
Continue with the first workflow or use the starter CLAUDE.md templates.
| Situation | Suggested route |
|---|---|
| New to Claude Code | Seven-module learning path |
| Already using the CLI | Core Concepts, then Context Engineering |
| Senior developer or tech lead | Methodologies, Agent Harness Engineering, then Production Safety |
| Engineering manager or CTO | Adoption Approaches, Team Metrics, then Subscription Strategy |
| Security or platform role | Security Hardening, Enterprise Governance, then Observability |
| Product manager or designer | Product Manager Guide or Design-to-Code Workflow |
| Non-developer knowledge worker | Claude Cowork Guide |
For a personalized route, use the repository onboarding prompt:
claude "Fetch and follow the onboarding instructions from: https://raw.githubusercontent.com/FlorianBruniaux/claude-code-ultimate-guide/main/tools/onboarding-prompt.md"
An agent is one component of a larger system. The surrounding harness controls context, tools, permissions, state, stopping conditions, recovery, and evaluation.
| Resource | Decision it supports |
|---|---|
| Agent Harness Engineering | Identify the controls required around an agent loop |
| Loop & Graph Engineering | Choose bounded feedback loops or explicit workflow graphs |
| AI Design Patterns | Explain an agent design with the GoF, integration, and resilience patterns developers know |
| Agent Harness Map | Distinguish runtimes, orchestrators, frameworks, control planes, and support tools |
| Agentic Tools | Compare selected coding agents and orchestration products |
| Agent Evaluation | Test behavior, regressions, and task-level outcomes |
| Harness Glossary | Align terminology across design and review |
| AI Concept Boundaries | Resolve seven common confusions with repository examples and comprehension checks |
Context quality affects every tool call and decision. Start with project instructions, add specialized context only when a recurring task needs it, and test whether the extra material changes behavior.
| Resource | Focus |
|---|---|
| Context Engineering | Context budget, modular instructions, assembly, and measurement |
| Memory Systems | Native memory, cross-session systems, team sharing, and retention risks |
| Context Engineering Tools | Output compression, retrieval, gateways, and context inspection |
| Context Audit | Measure a project's context architecture |
| Team AI Instructions | Maintain shared instructions across a development team |
| Goal | Workflow |
|---|---|
| Implement with tests first | TDD with Claude |
| D
Only the beginning is shown; read the rest in the repo