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Plumb

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

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "plumb": {
      "command": "npx",
      "args": [
        "-y",
        "plumb"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Documentation Overview

CI Go Reference Go Report Card License: MIT

plumb

IDE intelligence for agents β€” guardrails for unattended work, coordination for fleets.

Plumb is an MCP server that gives a coding agent the intelligence layer of an IDE β€” LSP-backed semantics, a tree-sitter code index, and project memory β€” 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 β€” 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 β€” every write is staged in a temp file and renamed into place. No partial writes, ever. Symlink-aware, CRLF-tolerant.
  • Per-path locking β€” the daemon serialises concurrent writes to the same file across every session and chat window. No races.
  • Multi-file transactions β€” apply edits across dozens of files with guaranteed atomic rollback if any step fails.
  • Crash-resilient daemon β€” 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 β€” mtime/sha guards catch stale edits before they clobber newer changes.

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

daemon-respawn.sh: the daemon is killed mid-session and the agent's next edit still succeeds

2. Multi-agent coordination

One daemon serves every agent you run β€” 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) β€” 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 β€” no change applied] β€” so "a peer is working here" and "this landed" are distinguishable at a glance.)
  • An agent-to-agent mailbox (on by default, same workspace) β€” 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) β€” 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) β€” 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 β€” the write-safety above never depends on agents cooperating. Reference: Cross-agent sharing in the tool docs and the [collab] config section.

3. Semantic intelligence

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

  • LSP-backed refactors β€” rename_symbol, replace_symbol_body, safe_delete_symbol understand scope, types, and references.
  • Real diagnostics inline β€” actual gopls/pyright output is appended to every write, so the agent learns it broke the build immediately.
  • Symbol search β€” scoped to your code, no stdlib or dependency noise.

4. Context efficiency & safety controls

  • Read only what you need β€” symbols or line ranges, not 2,000-line files.
  • Scoped access you control β€” 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 β€” session_start returns workspace, branch, recent commits, diagnostics, and project memory.

See the measured, reproducible numbers behind this: docs/use-cases.md β€” reading one function is 2.9×–33.4Γ— 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 1.31Γ— more payload than reading the files natively (down from 1.32Γ—, but still a loss β€” 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 β€” from zero to your first answer:

1. Install

sh
# Homebrew (macOS + Linux) β€” 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 β€” on first run you may need xattr -d com.apple.quarantine ./plumb, or right-click β†’ Open. Homebrew installs avoid this.

2. Connect your agent

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

plumb setup writes the MCP config for you β€” 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:

sh
cd your/project
claude "Use plumb to orient in this repo (session_start), then show me
everywhere <Handler> 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 β€” actual call sites and blast radius β€” instead of guessing from file dumps. It's read-only; nothing is modified. (Any connected agent works β€” 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 β†’ 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 β€” 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.<lang>] 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 β€” 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 β€” 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.

Read the full README β†’View source on GitHub β†’

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Frequently Asked Questions about Plumb

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "plumb": { "command": "npx", "args": ["-y", "Plumb"] } }

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
Last updatedSep 7, 2026
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27Quality signal: Emerging Β· 27/100How this signal is calculated β–Ύ
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Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20
Documentation & tools11/30
Adoption & activity1/15
Community engagement0/10

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