Search the Claude Code Ultimate Guide and machine-readable references from any MCP client.
io.github.FlorianBruniaux/claude-code-guide MCP Server
This MCP server enables an MCP client to search the “Claude Code Ultimate Guide” and related machine-readable references. It is positioned as a coding-assistance resource focused on Claude Code, with content intended to be discoverable programmatically from other tools.
🛠️ Key Features
Search support for the Claude Code Ultimate Guide
Access to machine-readable references
Published under io.github.FlorianBruniaux/claude-code-guide
🚀 Use Cases
Claude Code–related guidance retrieval from any MCP client
Developer workflows needing references via an MCP server
Finding information tied to topics such as agentic-coding and ai-pair-programming
⚡ Developer Benefits
Integrates guide content into tool-driven environments (MCP clients)
Enables reference lookup for ai-assistant and coding-assistant scenarios
Topic coverage includes best-practices, prompt-engineering, and ai-security
⚠️ Limitations
Server description and excerpt do not specify available tools, authentication, or query methods beyond “search.”
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.
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.
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.
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.
Start
Install Claude Code
Choose one installation method:
bash
# npm, macOS, Linux, or Windows
npm install -g @anthropic-ai/claude-code
# macOS with Homebrew
brew install claude-code
# macOS or Linux native installer
curl -fsSL https://claude.ai/install.sh | sh
Windows PowerShell also supports:
powershell
irm https://claude.ai/install.ps1 | iex
Verify the installation and authenticate:
bash
claude --version
claude doctor
claude auth login
The Quick Start chapter documents installation alternatives, authentication, updates, permission modes, and common first-day failures.
Complete a first task
Open a small repository with a clean or understood Git state, then start Claude Code:
bash
cd your-project
claude
Give Claude a bounded request that includes the expected result and verification:
text
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:
markdown
# Project instructions## Commands- Test: `npm test`- Lint: `npm run lint`## Boundaries- Do not edit generated files.
- Do not change dependencies without approval.
- Run the relevant tests before claiming completion.
For a personalized route, use the repository onboarding prompt:
bash
claude "Fetch and follow the onboarding instructions from: https://raw.githubusercontent.com/FlorianBruniaux/claude-code-ultimate-guide/main/tools/onboarding-prompt.md"
Build
Agent engineering
An agent is one component of a larger system. The surrounding harness controls context, tools, permissions, state, stopping conditions, recovery, and evaluation.
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.
Browse every workflow for task management, GitHub Actions, production reliability, event-driven agents, design-to-code, PDF generation, search, and team instructions.
Choose the smallest interface
Claude Code can call local commands, skills, agents, hooks, plugins, and MCP servers. More infrastructure adds setup, permissions, failure modes, and maintenance.
Security claims and threat counts change as sources are added or corrected. Use the linked database and guides as the current source instead of copying their counts into project documentation.
A green structural check proves only what it inspected. Runtime behavior, task acceptance, security boundaries, and business outcomes require separate evidence.
The economics pages separate observed costs from estimates and scenarios. Recalculate them with your workload, acceptance criteria, review effort, and risk constraints.
The list operations and search index use bundled content. Section, example, cheatsheet, changelog, digest (get_digest), and threat tools can fetch GitHub content and write a 24-hour local cache. The official-doc initialization and refresh tools fetch Anthropic documentation and write separate local snapshots.
Use reference.yaml when the assistant needs structured topic routes and links into the full guide. Maintenance instructions belong in the machine-readable documentation, not in this README.
Complementary ecosystem
No single repository needs to cover learning, installation, curation, reference material, and every specialized interface. Choose the resource that matches the current task.
Use the changelog for the complete history. The README should expose only a small current selection.
Languages and translations
English is the canonical edition. French is maintained in this repository. Simplified Chinese, Ukrainian, and Latin American Spanish are independent community editions with separate update schedules.
Corrections, missing evidence, broken links, examples, quiz questions, and documentation improvements are welcome. Read CONTRIBUTING.md before opening a pull request.
Useful contribution routes:
Report an incorrect or outdated claim through GitHub Issues.
