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。使用 Google 登录即可撰写评价。
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 0.27.0i★ 4i–
注册名称io.github.plumbkit/plumb

安装方法

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.

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: 开发者工具

安装

选择你使用的 AI 应用,然后复制设置。

通过 3/3 项检查 · 在你的电脑上运行

第一步:你用哪个 AI?

选择你用的应用,步骤会显示在下方。

Claude 暂时无法连接 Plumb

开发者尚未在 MCP 注册表中填写安装方式

ChatGPT 暂时无法连接 Plumb

开发者尚未在 MCP 注册表中填写安装方式

你可以改用这些方式

B · 开发者工具 类中能连接 ChatGPT 的其他服务器

从同类中使用较多的里挑选,仅限用地址即可连接、无需密钥的

Claude Code 暂时无法连接 Plumb

开发者尚未在 MCP 注册表中填写安装方式

Cursor 暂时无法连接 Plumb

开发者尚未在 MCP 注册表中填写安装方式

VS Code 暂时无法连接 Plumb

开发者尚未在 MCP 注册表中填写安装方式

其他支持 MCP 的应用(如 Windsurf、Zed、Gemini CLI)添加方式各不相同,请在应用列表中查看

查看所有支持 MCP 的应用 →

JSON 设置在下方“开发者专用”中

卡住了?问问正在用 Plumb 的人💬 讨论 →

一览

每周下载量i
不在 npm/PyPI 上
连接方式
–
最新版本i
0.27.0
发布到注册中心i
2026年11月11日
代码最后更新i
2026年11月11日
作者
plumbkit
注册状态
活跃

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11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

  • ✓ 通过

    仍在维护

    代码最后更新于昨天

  • ✓ 通过

    有许可证

    使用 MIT

  • – 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

讨论

提问、分享技巧或报告无法使用。按“有帮助”数量排序。

还没有帖子,欢迎第一个提问或分享。

此处内容由用户撰写,不代表 PopNx 团队。

使用 Google 登录后发帖

用户评价

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与“开发者工具”中的其他服务器比较i

  • 星标数多于此分类中其他 5773 个服务器的 83%
  • 发布到注册中心的时间比此分类中其他 5773 个服务器的 97% 更新
  • 基础检查结果等于或优于此分类中其他 5773 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 3 项适用的基础检查中通过了 3 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 仓库最后更新于昨天,最新版本(0.27.0)于昨天进入注册中心。

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。

有什么可以替代它?

同一分类中有:REA, Netdata, Front-End Checklist

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:↓ 每周下载量i★ 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

REA

Reverse engineer anything from your terminal or agent with one CLI and MCP server.

作者:morluto广泛使用↓ 38.9万/周★ 45.1万17天前更新

在你的电脑上运行

Netdata

Real-time infrastructure monitoring with metrics, logs, alerts, and ML-based anomaly detection.

作者:netdata广泛使用★ 8.1万7天前更新

在云端运行

Front-End Checklist

Review frontend code and live pages against 386 quality-gated web development rules.

作者:thedaviddias广泛使用★ 7.5万38天前更新

在云端运行

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