原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Plumb

作者:plumbkit版本 0.26.2i★ –i–
注册名称io.github.plumbkit/plumb

安装

概览

作者提供的说明(英文原文)

LSP-backed IDE intelligence plus concurrency-safe, transactional edits for AI coding agents.

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。

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: –
  • 传输方式:
  • 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。

作者没有在注册中心列出安装信息。请查看下方作者的 README。

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 plumbkit 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 32489 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32489 个服务器的 64% 更新
  • 基础检查结果等于或优于此分类中其他 32489 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

Plumb 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(0.26.2)于21天前进入注册中心。

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。

有什么可以替代它?

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

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

Whisper

作者:whisper-sec

One routable IPv6 per AI agent, verifiable from the DNS root. Keyless tools need no signup.

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。

IDE intelligence for agents — guardrails for unattended work, coordination for fleets.

Plumb is an MCP server that gives a coding agent the intelligence layer of an IDE — LSP-backed semantics, a tree-sitter code index, and project memory — inside guardrails: atomic, lock-serialised writes with transactional rollback, scoped filesystem and git access, and a daemon that survives its own crashes. And because every agent you run shares that one daemon, plumb is also the coordination layer between them: peers see the writes others made, message each other, and hand off work instead of duplicating it. A single binary; nothing else to install.


Why Plumb

LLM agents usually work by reading whole files into the context window — token-heavy, lossy at scale, blind to symbol semantics, and unsafe to let loose on a real repo. Plumb is built on four pillars, in priority order.

1. Reliability & write-safety

Leaving an agent to edit a codebase for an hour is only viable if writes can't corrupt files and a crash can't wedge your session.

  • Atomic I/O — every write is staged in a temp file and renamed into place. No partial writes, ever. Symlink-aware, CRLF-tolerant.
  • Per-path locking — the daemon serialises concurrent writes to the same file across every session and chat window. No races.
  • Multi-file transactions — apply edits across dozens of files with guaranteed atomic rollback if any step fails.
  • Crash-resilient daemon — plumb serve is a reconnecting proxy. If the daemon crashes or hangs, it respawns one and replays the handshake; the agent never notices. In-flight writes are never silently re-run.
  • Optimistic concurrency — mtime/sha guards catch stale edits before they clobber newer changes.

See it run: docs/demos/ — two-agents-one-file.sh (a stale write is refused, nothing is lost) and daemon-respawn.sh (below — the daemon is killed mid-session; the agent's next edit still succeeds):

2. Multi-agent coordination

One daemon serves every agent you run — which makes it the natural place for agents to *see and talk to* each other, not merely avoid each other's writes. Locks stop two agents corrupting a file; coordination stops them duplicating a task, rebasing onto a function signature a peer is mid-rewrite of, or shipping a change a peer's in-flight work is about to invalidate.

  • Peer awareness (on by default) — workspace_sessions names every active session and the writes it made, as the daemon recorded them. Recorded activity, not another agent's say-so: an agent about to start a task can see that a peer is already in those files. (Read-only operations never appear, and a write that failed or was refused is kept but marked [failed — no change applied] — so "a peer is working here" and "this landed" are distinguishable at a glance.)
  • An agent-to-agent mailbox (on by default, same workspace) — leave_note / check_messages give sessions a threaded channel: hand a change to the peer already rewriting those files, or ask a peer to *measure* a behaviour instead of assuming it. Messages ride on ordinary tool results, so a working agent receives them without polling.
  • Advisory intents (opt-in: [collab] intents) — share_intent declares what an agent is working on; a peer whose write touches a claimed path gets a hint at the moment of the would-be collision. Intents are deliberately labelled as unverified claims, kept distinct from the daemon-recorded activity feed, and never block anything.
  • Durable findings (opt-in: [collab] knowledge_handoff) — share_findings turns what an agent just learned into a searchable, secret-scrubbed project memory immediately, so the knowledge outlives the session that produced it.

Coordination is advisory by design — the write-safety above never depends on agents cooperating. Reference: Cross-agent sharing in the tool docs and the [[collab] config section](docs/configuration.md#collab--cross-agent-sharing).

3. Semantic intelligence

The same primitives your editor has, exposed as structured tools:

  • LSP-backed refactors — rename_symbol, replace_symbol_body, safe_delete_symbol understand scope, types, and references.
  • Real diagnostics inline — actual gopls/pyright output is appended to every write, so the agent learns it broke the build immediately.
  • Symbol search — scoped to your code, no stdlib or dependency noise.
4. Context efficiency & safety controls
  • Read only what you need — symbols or line ranges, not 2,000-line files.
  • Scoped access you control — a per-connection path allowlist (read-only vs read-write roots) plus tiered git gating (destructive and network operations are off by default and need explicit confirmation). See SECURITY.md.
  • One-round-trip bootstrap — session_start returns workspace, branch, recent commits, diagnostics, and project memory.

See the measured, reproducible numbers behind this: docs/use-cases.md — reading one function is 2.9×–33.4× less context than the whole file (the ratio is how much of the file you didn't need), and find_references returns the real call sites where a text search is 60% noise. The page publishes the losses too: read_multiple_files costs 1.31× more payload than reading the files natively (down from 1.32×, but still a loss — see Scenario 10 for why it isn't smaller). Every figure is regenerated by scripts/measure-use-cases.py.


Get started

Plumb is a single binary — from zero to your first answer:

1. Install

# Homebrew (macOS + Linux) — recommended

brew install plumbkit/plumb/plumb

or with Go

go install github.com/plumbkit/plumb/cmd/plumb@latest

or grab a prebuilt binary: https://github.com/plumbkit/plumb/releases

macOS note: prebuilt binaries are not yet notarised — on first run you may

need xattr -d com.apple.quarantine ./plumb, or right-click → Open. Homebrew

installs avoid this.

2. Connect your agent

plumb setup claude-code      # also: claude-desktop, codex, gemini, cursor, …

plumb setup writes the MCP config for you — no hand-editing JSON.

3. Open your project and try it

Make sure the language server you need is on your $PATH (gopls for Go, pyright for Python, …), then point your agent at a real question. In Claude Code:

cd your/project

claude "Use plumb to orient in this repo (session_start), then show me everywhere is called and what would break if I changed its signature."

Plumb resolves the workspace and runs session_start for orientation, then answers with real LSP and topology data — actual call sites and blast radius — instead of guessing from file dumps. It's read-only; nothing is modified. (Any connected agent works — just paste the prompt.)

No go.mod/pyproject.toml and not a git repo? Run plumb init once to pin

the workspace root (it also seeds .plumb/context.md and project config).

Full walkthrough → docs/getting-started.md.


Language support (honest version)

Plumb negotiates LSP capabilities per language and also ships a built-in tree-sitter index for search and navigation with no language server. Support comes in tiers — we'd rather be precise than claim a big number.

TierLanguagesWhat you get
First-class (CI-tested, real-binary integration)Go (gopls), Python (pyright)Full LSP: definitions, references, rename, diagnostics, hierarchies + all write tools
ValidatedJava (jdtls), Rust (rust-analyzer), Swift (sourcekit-lsp), TypeScript/JS (typescript-language-server), Zig (zls), Kotlin (kotlin-lsp), HTML (vscode-html-language-server)Full LSP; just put the server on $PATH and it activates automatically (exclude any language with [lsp. ] enabled = false). HTML carries one caveat: that server has no filesystem access, so it answers only from documents already opened
Search & navigation (tree-sitter, no LSP needed)31+ incl. JS/TS/TSX, Ruby, C, C#, Elixir, Scala, PHP, JSON, CSS, SCSS, XML, Lua, C++, Objective-C, Dart, Bash, SQL, HCL, Dockerfile, TOML, YAML, MarkdownRanked symbol search, outlines, graph exploration via the Topology index

Real-binary validation has been exercised on macOS and Linux — as of 2026-08-21, all nine adapters pass their integration tests against real server binaries on both. Details, including three toolchain traps that look like adapter bugs, are in docs/adding-an-lsp.md. Windows is tracked but not yet supported — the daemon's Unix-socket architecture needs a port.


How it works

plumb serve is a thin, reconnecting stdio proxy. The real work happens in one shared background daemon, so language servers stay warm across chats.

flowchart TD

A1["Claude"] --> S1["plumb serve *"] A2["Codex"] --> S2["plumb serve *"] A3["Gemini"] --> S3["plumb serve *"] S1 --> K["plumb.sock"] S2 --> K S3 --> K K --> D["plumb daemon "] D --> SDB[("stats.db * global — all projects")] D --> G["gopls → /projects/foo"] D --> P["pyright → /projects/bar"] G --> F1[("/projects/foo/.plumb/ * topology.db · memory.db")] P --> F2[("/projects/bar/.plumb/ * topology.db · memory.db")]

* plumb serve is a reconnecting proxy — if the daemon crashes or hangs it respawns one and replays the handshake, so your session survives without the agent noticing.

** one shared process, reused across every conversation.

*** SQLite. One global stats.db (tool stats + episodic summaries); two per-project indexes under each workspace's .plumb/ — topology.db (the code graph) and memory.db (memory search). Schema details → docs/architecture.md.

Servers stay warm across chats, per-path locks are shared across every connection, and symbol indexes update live after each write. Full architecture → docs/architecture.md.


Monitoring (TUI)

Run plumb with no arguments for a live dashboard — see what your agent is doing in real time: every tool call as it happens, daemon health, per-tool stats, and streaming logs you can follow and filter. The fastest way to catch a runaway loop or confirm an edit landed.


Core capabilities

Plumb exposes 61 tools. The ones you'll use constantly:

session_start · workspace_symbols · get_definition · find_references · rename_symbol · edit_file · transaction_apply · diagnostics

The rest cover filesystem reads/writes, LSP hierarchies, tiered git, an optional local Topology index (ranked search + blast-radius/route analysis, no language server needed), durable per-project memory, and cross-agent coordination (peer sessions, an age

只显示了开头部分;其余内容请在仓库中阅读

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