Prototype · Preview: every server in the official registry, synced every 30 minutes. Reviews and accounts come in a later step.
PopNx MCPMCP servers for people who use AI · explained in plain words

Patchloom

by patchloomversion 0.37.7i★ –iRuns on your computer
Registry nameio.github.patchloom/patchloom

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

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

Run this in your terminal

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

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

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.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

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

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.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

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 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account patchloom, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32583 servers in this category
  • Published to the registry more recently than 96% of the other 32583 servers in this category
  • Basic checks equal to or better than 100% of the other 32583 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Patchloom safe?

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.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

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).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.37.7) reached the registry yesterday.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Rust, Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, sync. labs

Alternatives

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

Spec Driven Development

by formulahendry

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

Runs on your computer★ 440MITUpdated 14 months ago
Install

Remote Desktop Commander

by desktop-commander

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

Runs in the cloud★ 211Updated yesterday
Install

sync. labs

by synchronicity-labs

Lipsync videos, dub them into other languages, make talking videos and open sync. Studio.

Computer or cloudUpdated today
Install

README from the maker

Open the README

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.

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?](#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)


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:

  1. Syntax corruption. The agent uses text replacement on JSON, YAML, or TOML and produces invalid output (mismatched braces, broken indentation, lost comments).
  2. 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.
  3. 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
ProblemHow patchloom solves it
Syntax corruptiondoc commands parse the file, change the value by selector path, and write valid output. Comments and formatting are preserved. No regex needed.
Round-trip taxbatch and tx combine N operations into 1 tool call. Six file edits become one command with atomic rollback on failure.
Platform fragmentationSingle 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
CapabilityWhat it doesExample
Parser-backed editsEdit JSON/YAML/TOML by selector, preserving comments and formattingdoc set config.yaml db.port 5432 --apply
Batch N files in 1 callbatch and tx combine operations into one tool call with rollbackbatch --apply < ops.txt
Comment preservationYAML/TOML comments survive all edits, including array resizingdoc append config.yaml tags '"v2"' --apply
Heading-aware markdownEdit sections, tables, and bullets by heading, not line number`md table-append README.md --heading "API" --row "\new \row \" --apply`
AST-aware code opsList, rename, replace, and analyze symbols across 20 languagesast rename src/ --old old_name --new new_name --apply
Atomic rollbackstrict: true reverts every file if format or validate steps failtx plan.json --apply
MCP serverExpose all operations as structured MCP tool callspatchloom mcp-server
Optional CLI sandboxReject ../ / absolute path escapes from --cwd on reads and writes (off by default; MCP always on)patchloom --cwd --contain search … / create … --apply
Cross-platformIdentical 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:

TaskUse patchloom?Why
Edit a JSON/YAML/TOML value by selectorYesParser guarantees valid output, preserves comments
Edit 3+ files in one taskYesbatch/tx eliminates round-trips
Append a row to a markdown tableYesHeading-aware, no line number guessing
Read a single fileNoNative read_file is faster
Simple text searchNoNative grep is faster
Single-file text replacementNoNative 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

Only the beginning is shown; read the rest in the repo

Ask PopNx