Patchloom

Name: Patchloom
Author: patchloom

作者：patchloom版本 0.37.7i★ –i在你的电脑上运行

注册名称io.github.patchloom/patchloom

安装

概览

作者提供的说明（英文原文）

Agent-safe structured edits: JSON/YAML/TOML/md/AST, dry-run, batch/tx. Not a filesystem MCP.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数：意见、测量和人气是不同的东西。

用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
我们的基础检查i1 项中通过 1 项依据公开信息检查；尚未扫描代码
使用情况i尚未统计★ –

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

连接方式: 在你的电脑上运行
传输方式: stdio
分类: 其他

安装

选择你使用的 AI 应用，然后复制设置。

安装之前

基础检查：1 项中通过 1 项
在你的电脑上运行，拥有你的用户账户的权限（文件、网络、应用）。
注册中心没有列出需要填写的密钥。

你需要

npm已安装 Node.js（用于 npx 命令）

你用的是哪个应用？

ClaudeClaude CodeCursorVS CodeChatGPT

在上方选择你的应用。我们会记住它，下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config，把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "patchloom": {
      "command": "npx",
      "args": [
        "-y",
        "patchloom",
        "mcp-server"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add patchloom -- npx -y patchloom mcp-server

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json，或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "patchloom": {
      "command": "npx",
      "args": [
        "-y",
        "patchloom",
        "mcp-server"
      ]
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "patchloom": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "patchloom",
        "mcp-server"
      ]
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

这个服务器在你的电脑上运行，而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上，无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。

它能做什么

它在你的电脑上运行；安装后，工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 patchloom 验证，该账户拥有此仓库
… 尚未检查
仍在维护
我们还没有从 GitHub 读取这个仓库
… 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
– 不适用
端点有响应
它在你的电脑上运行，没有互联网端点
– 不适用
使用 OAuth 登录
在你的电脑上运行，改用本地设置
… 尚未检查
工具描述中没有隐藏指令
它在你的电脑上运行；我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

星标数多于此分类中其他 32380 个服务器的 0%
发布到注册中心的时间比此分类中其他 32380 个服务器的 99% 更新
基础检查结果等于或优于此分类中其他 32380 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

常见问题

Patchloom 安全吗？

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前，请先看看这个服务器要求哪些权限，并使用只具备所需权限的密钥。

它需要哪些密钥或代码？

注册中心没有列出必需的密钥，不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端？

它在你的电脑上运行。你的 AI 应用会在需要时启动它，数据不会经过作者的服务器（除非它自己调用在线服务）。

它还在维护吗？

GitHub 仓库最后更新于–，最新版本（0.37.7）于今天进入注册中心。

哪些应用可以使用它？

支持 MCP 的应用，例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Rust, Node.js。

有什么可以替代它？

同一分类中有：Spec Driven Development, Remote Desktop Commander, Dechonet MCP

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者：formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新

安装

Remote Desktop Commander

作者：desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211昨天更新

安装

Dechonet MCP

作者：node-man

30 security tools for AI agents: phishing links, exposure maps, DNS, SSL, PQC, history, pivots.

电脑或云端今天更新

安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Patchloom

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

Batch 6 file edits into a single tool call

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?

The problem

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:

Syntax corruption. The agent uses text replacement on JSON, YAML, or TOML and produces invalid output (mismatched braces, broken indentation, lost comments).
Round-trip tax. Editing 6 files means 6 separate tool calls. Each one waits for the LLM to generate, execute, read the result, and plan the next call.
Platform fragmentation. On Linux the agent uses sed, jq, grep. On Windows, none of those exist. The agent falls back to verbose PowerShell or makes errors with unfamiliar syntax.

How patchloom solves each one

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.

What changes with patchloom

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

Key capabilities

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

When to use patchloom vs native tools

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

Correctness over speed

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.

Install

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

crates.io (requires Rust 1.95+, includes MCP server)

cargo install patchloom

npm / npx (downloads the platform binary from GitHub Releases)

npx patchloom --version

or: npm install -g patchloom

# 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 Registry name: mcp-name: io.github.patchloom/patchloom

Editor extension

Install 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.

Quick start

1. Set up your project

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

Or tailor the output:

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

只显示了开头部分；其余内容请在仓库中阅读

Patchloom

概览

PopNx MCP 的三大支柱

它能帮你做什么

安装

安装之前

它能做什么

基础检查i

作者与仓库一致

仍在维护

有许可证

端点有响应

使用 OAuth 登录

工具描述中没有隐藏指令

与“其他”中的其他服务器比较i

常见问题

替代选择

Spec Driven Development

Remote Desktop Commander

Dechonet MCP

作者的 README

Patchloom

Batch 6 file edits into a single tool call

Why Patchloom?

The problem

How patchloom solves each one

What changes with patchloom

Key capabilities

When to use patchloom vs native tools

Correctness over speed

Install

crates.io (requires Rust 1.95+, includes MCP server)

npm / npx (downloads the platform binary from GitHub Releases)

or: npm install -g patchloom

Editor extension

Quick start

1. Set up your project

Or tailor the output: