Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Agent-safe structured edits: JSON/YAML/TOML/md/AST, dry-run, batch/tx. Not a filesystem MCP.
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": {
"patchloom": {
"command": "npx",
"args": [
"-y",
"patchloom",
"mcp-server"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add patchloom -- npx -y patchloom mcp-server프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"patchloom": {
"command": "npx",
"args": [
"-y",
"patchloom",
"mcp-server"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"patchloom": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"patchloom",
"mcp-server"
]
}
}
}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 patchloom 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(0.37.7)은 어제 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Rust, Node.js도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, FactLot
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.
Cited CRE facts and deterministic calculators for agents: rent, CAM, debt sizing, IRR, parcel IDs.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
One binary. Every platform. Structured file edits for AI agents.
Patchloom is a single-binary CLI that gives AI coding agents safe, structured file editing on any operating system. It edits JSON, YAML, and TOML by selector (not regex), preserves comments, understands code structure across 20 languages, batches multiple file edits into one tool call, and works identically on Linux, macOS, and Windows.
Not a generic filesystem MCP. Default MCP filesystem servers read/write files as text. Patchloom adds dry-run previews, parser-backed config and markdown edits, AST ops, multi-file batch/tx with undo, and stable error_kind peels for hosts. Full coding agents (Claude Code, Codex, Cursor) own the loop; Patchloom is the tool layer they (or a Rust embedder) call.
# Edit a YAML value by selector without breaking comments or formatting
patchloom doc set config.yaml database.port 5432 --apply
patchloom batch --apply <<'EOF' doc.set package.json version "2.0.0" doc.set config.yaml app.version "2.0.0" doc.set config.toml project.version "2.0.0" replace README.md "1.0.0" "2.0.0" replace CHANGELOG.md "1.0.0" "2.0.0" file.create VERSION "2.0.0" EOF
[Why Patchloom?](#why-patchloom) | [Install](#install) | [Quick start](#quick-start) | [Commands](#commands) | [Comparison](#how-patchloom-compares) | [When to use what](#when-to-use-what) | [Architecture](#how-it-works-with-your-ai-agent) | [Status](#status)
AI agents edit files through tool calls. Each call is a round-trip back to the LLM. When a task touches config files, that process has three failure modes:
sed, jq, grep. On Windows, none of those exist. The agent falls back to verbose PowerShell or makes errors with unfamiliar syntax.| Problem | How patchloom solves it |
|---|---|
| Syntax corruption | doc commands parse the file, change the value by selector path, and write valid output. Comments and formatting are preserved. No regex needed. |
| Round-trip tax | batch and tx combine N operations into 1 tool call. Six file edits become one command with atomic rollback on failure. |
| Platform fragmentation | Single static binary with zero dependencies. Same commands, same flags, same behavior on Linux, macOS, and Windows. |
Without patchloom (6 tool calls)
Agent: edit file 1 ─── tool call ───▶ 15s
Agent: edit file 2 ─── tool call ───▶ 15s Agent: edit file 3 ─── tool call ───▶ 15s Agent: edit file 4 ─── tool call ───▶ 15s Agent: edit file 5 ─── tool call ───▶ 15s Agent: edit file 6 ─── tool call ───▶ 15s Total: ~90s
With patchloom batch (1 tool call)
Agent: batch with
all 6 edits ─── tool call ───▶ 25s
5 round-trips saved Total: ~25s
| Capability | What it does | Example | |||
|---|---|---|---|---|---|
| Parser-backed edits | Edit JSON/YAML/TOML by selector, preserving comments and formatting | doc set config.yaml db.port 5432 --apply | |||
| Batch N files in 1 call | batch and tx combine operations into one tool call with rollback | batch --apply < ops.txt | |||
| Comment preservation | YAML/TOML comments survive all edits, including array resizing | doc append config.yaml tags '"v2"' --apply | |||
| Heading-aware markdown | Edit sections, tables, and bullets by heading, not line number | `md table-append README.md --heading "API" --row "\ | new \ | row \ | " --apply` |
| AST-aware code ops | List, rename, replace, and analyze symbols across 20 languages | ast rename src/ --old old_name --new new_name --apply | |||
| Atomic rollback | strict: true reverts every file if format or validate steps fail | tx plan.json --apply | |||
| MCP server | Expose all operations as structured MCP tool calls | patchloom mcp-server | |||
| Optional CLI sandbox | Reject ../ / absolute path escapes from --cwd on reads and writes (off by default; MCP always on) | patchloom --cwd --contain search … / create … --apply | |||
| Cross-platform | Identical behavior on Linux, macOS, Windows. No sed, jq, grep required. | Same binary everywhere |
Patchloom is not a replacement for all file operations. Its instructions tell agents exactly when to use it and when native tools are faster:
| Task | Use patchloom? | Why |
|---|---|---|
| Edit a JSON/YAML/TOML value by selector | Yes | Parser guarantees valid output, preserves comments |
| Edit 3+ files in one task | Yes | batch/tx eliminates round-trips |
| Append a row to a markdown table | Yes | Heading-aware, no line number guessing |
| Read a single file | No | Native read_file is faster |
| Simple text search | No | Native grep is faster |
| Single-file text replacement | No | Native search_replace is faster |
Patchloom is not faster than native tools for simple, single-file edits. Use native tools for those. But native text replacement cannot safely edit structured files: a sed on YAML can corrupt indentation, strip comments, or produce invalid syntax. doc set parses the file, changes the value by selector, and writes valid output. That guarantee is the point.
Where patchloom *is* faster is multi-file batching. Six file edits via native tools means six round-trips to the LLM. One batch call does the same work in a single round-trip.
Benchmark details (Claude Opus 4 via Grok Build, 11 tasks)
Task PL-CLI MCP Native
────────────────────── ────── ────── ────── search 18.5s 12.7s 13.9s ◀ ~same replace 36.1s 26.6s 26.1s ◀ ~same doc_set 30.9s 16.9s 13.7s ◀ native fastest md_table 15.5s 13.5s 15.3s ◀ MCP fastest tx_multi_file 41.4s 28.5s 22.9s ◀ native fastest batch_6_files 50.6s 46.6s 30.3s ◀ native fastest batch_mixed_ops 24.7s 13.6s 20.9s ◀ MCP fastest yaml_comment_preserve 18.1s 11.6s 16.1s ◀ MCP fastest md_insert 15.0s 11.7s 15.7s ◀ MCP fastest file_ops 26.0s 16.6s 17.2s ◀ ~same tidy 45.0s 30.3s 41.7s ◀ MCP fastest ────────────────────── ────── ────── ────── TOTAL 321.9s 228.5s 233.8s
MCP mode wins overall (228.5s vs 233.8s native) because structured tool calls skip shell syntax construction entirely. MCP wins 5/11 tasks; native wins 3/11; 3 are ties. CLI mode is always slowest due to shell construction overhead.
Prefer channels that track each GitHub Release (Homebrew, Scoop, crates, npm, Releases). On Windows, Scoop is recommended. winget (Patchloom.Patchloom) is published per release and is usually current after Microsoft's publish pipeline (winget source update if search is stale). Chocolatey often lags while community moderation runs.
# Homebrew (macOS/Linux)
brew install patchloom/tap/patchloom
cargo install patchloom
npx patchloom --version
# Scoop (Windows; recommended Windows channel)
scoop bucket add patchloom https://github.com/patchloom/scoop-bucket scoop install patchloom/patchloom
Pre-built binaries for Linux, macOS, and Windows are on the Releases page. See Installation for shell installer scripts, source builds, shell completions, and winget / Chocolatey notes.
mcp-name: io.github.patchloom/patchloomInstall the companion extension for VS Code, Cursor, Windsurf, or VSCodium:
The extension auto-discovers the CLI (or installs it for you), generates AGENTS.md, configures MCP servers, and adds Quick Actions to the command palette. See the Editor Extension guide for details.
patchloom init
This creates AGENTS.md in a new project or appends the rules to an existing agent instructions file, offers shell completions, and detects MCP configuration opportunities. Pass -y to skip confirmation prompts.
If you only want the rules text:
patchloom agent-rules >> AGENTS.md
patchloom agent-rules --mode mcp >> AGENTS.md # MCP-only (no CLI examples) patchloom agent-rules --platform windows >> AGENTS.md # Windows-only syntax
If .vscode/ or .cursor/ exists, init also prints ready-to-copy .vscode/mcp.json or .cursor/mcp.json snippets.
Your AI a
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요