Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Code intelligence MCP server — 80+ tools for navigation, impact analysis, and architecture
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"ckb": {
"command": "npx",
"args": [
"-y",
"@tastehub/ckb",
"mcp"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add ckb -- npx -y @tastehub/ckb mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"ckb": {
"command": "npx",
"args": [
"-y",
"@tastehub/ckb",
"mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"ckb": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@tastehub/ckb",
"mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 SimplyLiz 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(8.0.3)은 10개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, FlyDocs
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Spec-driven development workflow: your agent works issues, sessions and the status lifecycle.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Know your code. Change it safely. Ship with confidence.
CKB transforms your codebase into a queryable knowledge base. Ask questions, understand impact, find owners, detect dead code—all through CLI, API, or AI assistants.
Think of it as a senior engineer who knows every line of code, every decision, and every owner—available 24/7 to answer your questions.
| Question | Without CKB | With CKB |
|---|---|---|
| "What breaks if I change this?" | Grep and hope | Precise blast radius with risk score |
| "Who should review this PR?" | Guess from git blame | Data-driven reviewer suggestions |
| "Is this code still used?" | Delete and see what breaks | Confidence-scored dead code detection |
| "What tests should I run?" | Run everything (30 min) | Run affected tests only (2 min) |
| "How does this system work?" | Read code for hours | Query architecture instantly |
| "Who owns this code?" | Search CODEOWNERS manually | Ownership with drift detection |
| "Are there exposed secrets?" | Manual grep for patterns | Automated scanning with 26 patterns |
🔍 Understand — Semantic search, call graphs, usage tracing, architecture maps
⚡ Analyze — Impact analysis, risk scoring, hotspot detection, coupling analysis
🛡️ Protect — Affected test detection, breaking change warnings, PR risk assessment
🔐 Secure — Secret detection, credential scanning, security-sensitive code identification
👥 Collaborate — Ownership lookup, reviewer suggestions, architectural decisions (ADRs)
📊 Improve — Dead code detection, tech debt tracking, documentation coverage
🚀 Compound Operations — Single-call tools (explore, understand, prepareChange) reduce AI tool calls by 60-70%
🔗 Integrate — CLI, HTTP API, MCP for AI tools, CI/CD pipelines, custom scripts
# See what's risky in your codebase
ckb hotspots --format=human
ckb diff-summary --format=human
ckb audit --format=human
ckb arch --format=human
ckb status
| AI Assistants | CI/CD | Your Tools |
|---|---|---|
| Claude Code, Cursor, Windsurf, VS Code, Grok | GitHub Actions, GitLab CI | CLI, HTTP API, Scripts |
83% token reduction with smart presets—load only the tools you need.
# One command to connect to Claude Code
ckb setup
Building your own tools? Use CKB as a backend via CLI, HTTP API, or MCP. See the [Integration Guide](https://github.com/SimplyLiz/CodeMCP/wiki/Integration-Guide) for examples in Node.js, Python, Go, and shell scripts.
| Resource | Description |
|---|---|
| 📖 [Features Guide](https://github.com/SimplyLiz/CodeMCP/wiki/Features) | Complete feature list with examples |
| 💬 [Prompt Cookbook](https://github.com/SimplyLiz/CodeMCP/wiki/Prompt-Cookbook) | Real prompts for real problems |
| 🔌 [Integration Guide](https://github.com/SimplyLiz/CodeMCP/wiki/Integration-Guide) | Use CKB in your own tools and scripts |
| ⚡ [Impact Analysis](https://github.com/SimplyLiz/CodeMCP/wiki/Impact-Analysis) | Blast radius, affected tests, PR risk |
| 🔧 [CI/CD Integration](https://github.com/SimplyLiz/CodeMCP/wiki/CI-CD-Integration) | GitHub Actions, GitLab CI templates |
# Install globally
npm install -g @tastehub/ckb
npx @tastehub/ckb init
brew install simplyliz/ckb/ckb
Use the fully-qualified name. Homebrew 6.0 requires third-party taps to be trusted before it loads them; installing this way grants that trust for this one formula. Tapping first and installing by short name fails with
Refusing to load formula ... from untrusted tap.
git clone https://github.com/SimplyLiz/CodeMCP.git
cd CodeMCP go build -o ckb ./cmd/ckb
# 1. Initialize in your project
cd /path/to/your/project ckb init # or: npx @tastehub/ckb init
ckb index # auto-detects language and runs appropriate indexer
ckb setup # creates .mcp.json automatically
claude mcp add --transport stdio ckb -- npx @tastehub/ckb mcp
Token efficiency shown at startup:
CKB MCP Server v9.3.1
Active tools: 25 / 110 (22%) Estimated context: ~4k tokens Preset: core
Now Claude can answer questions like:
| Without CKB | With CKB |
|---|---|
| AI greps for patterns | AI navigates semantically |
| "I found 47 matches for Handler" | "HandleRequest is called by 3 routes via CheckoutService" |
| Guessing at impact | Knowing the blast radius with risk scores |
| Reading entire files for context | Getting exactly what's relevant |
| "Who owns this?" → search CODEOWNERS | Instant ownership with reviewer suggestions |
| "Is this safe to change?" → hope | Hotspot trends + impact analysis |
| Interface | Best For |
|---|---|
| [MCP](https://github.com/SimplyLiz/CodeMCP/wiki/MCP-Integration) | AI-assisted development — Claude, Cursor, Windsurf, VS Code, OpenCode, Grok |
| [CLI](https://github.com/SimplyLiz/CodeMCP/wiki/User-Guide) | Quick lookups from terminal, scripting |
| [HTTP API](https://github.com/SimplyLiz/CodeMCP/wiki/API-Reference) | IDE plugins, CI integration, custom tooling |
CKB uses SCIP indexes to understand your code. Think of it like a database that knows where every function is defined, who calls it, and how everything connects.
# 1. Generate an index (auto-detects language)
ckb index
ckb status
Without an index, CKB still works using tree-sitter parsing (basic mode), but with an index you get:
Not all languages are equal. CKB classifies languages into quality tiers based on indexer maturity:
| Tier | Quality | Languages |
|---|---|---|
| Tier 1 | Full support, all features | Go |
| Tier 2 | Full support, minor edge cases | TypeScript, JavaScript, Python |
| Tier 3 | Basic support, call graph may be incomplete | Rust, Java, Kotlin, C++, Ruby, Dart |
| Tier 4 | Experimental | C#, PHP |
Key limitations:
--infer-tsconfig flagcompile_commands.jsonRun ckb doctor --tier standard to check if your language tools are properly installed.
See [Language Support](https://github.com/SimplyLiz/CodeMCP/wiki/Language-Support) for indexer installation, known issues, and the full feature matrix.
Your index becomes stale when you make commits. CKB offers several ways to stay current:
| Method | Command | When to Use |
|---|---|---|
| Manual | ckb index | One-off updates, scripts |
| Watch mode | ckb index --watch | Auto-refresh during development |
| MCP watch | ckb mcp --watch | Auto-refresh in AI sessions |
| CI webhook | POST /api/v1/refresh | Trigger from CI/CD |
Quick start for AI sessions:
ckb mcp --watch # Auto-reindexes every 30s when stale
Check staleness:
ckb status
For Go projects, CKB uses incremental indexing—only changed files are processed, making updates fast.
See the [Index Management Guide](https://github.com/SimplyLiz/CodeMCP/wiki/Index-Management) for complete documentation.
| Feature | Description |
|---|---|
| Compound Operations | explore, understand, prepareChange — single-call tools that reduce AI overhead by 60-70% |
| Code Navigation | Semantic search, call graphs, trace usage, find entrypoints |
| Impact Analysis | Blast radius, risk scoring, affected tests, breaking changes (compareAPI) |
| Architecture | Module overview, ADRs, dependency graphs, explain origin |
| Ownership | CODEOWNERS + git blame, reviewer suggestions, drift detection |
| Code Quality | Dead code detection (findDeadCode), coupling analysis, complexity |
| Security | Secret detection, credential scanning, allowlists |
| Documentation | Doc-symbol linking, staleness detection, coverage metrics |
| Multi-Repo | Federation, API contracts, remote index serving |
| Runtime | OpenTelemetry integration, observed usage, production dead code |
| Streaming | SSE streaming for findReferences, searchSymbols with real-time progress |
| Automation | Daemon mode, watch mode, webhooks, incremental indexing |
📖 [Full Features Guide](https://github.com/SimplyLiz/CodeMCP/wiki/Features) — Detailed documentation with examples
📋 [Changelog](https://github.com/SimplyLiz/CodeMCP/blob/main/CHANGELOG.md) — Version history
CKB review runs 21 quality checks in 5 seconds — secrets, breaking changes, dead code, complexity, test gaps, bug patterns, and more. Zero tokens, zero API calls.
When your AI assistant (Claude Code, Cursor, Windsurf) reviews a PR, it calls CKB first and gets structured analysis in ~1k tokens. Then it only reads the files that matter — saving 50-80% of tokens on large PRs.
ckb review --base=main # Human-readable review
ckb review --base=main --ci # CI mode (exit codes) ckb review --base=main --post=123 # Post as PR comment
Works in CI without any LLM:
- run: npx @tastehub/ckb review --base=main --ci --format=sarif > review.sarif
| Without CKB | With CKB | |
|---|---|---|
| LLM tokens on 100-file PR | ~200k | ~50k |
| Files LLM reads
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요