Plumb
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。
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
- Sentry✓ ChatGPT
- Front-End Checklist✓ ChatGPT
- Compiler Explorer✓ ChatGPT
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
一览
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。
用户评价
还没有评价
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
Netdata
Real-time infrastructure monitoring with metrics, logs, alerts, and ML-based anomaly detection.
Front-End Checklist
Review frontend code and live pages against 386 quality-gated web development rules.
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 serveis 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_sessionsnames 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_messagesgive 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_intentdeclares 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_findingsturns 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_symbolunderstand scope, types, and references. - Real diagnostics inline — actual
gopls/pyrightoutput 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_startreturns 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.tomland not a git repo? Runplumb initonce to pin
the workspace root (it also seeds
.plumb/context.mdand 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.
| Tier | Languages | What you get |
|---|---|---|
| First-class (CI-tested, real-binary integration) | Go (gopls), Python (pyright) | Full LSP: definitions, references, rename, diagnostics, hierarchies + all write tools |
| Validated | Java (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, Markdown | Ranked 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