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PopNx MCPAI를 쓰는 사람을 위한 MCP 서버 · 쉬운 말로 설명해요

Kawa Code

제작자: kawacode-ai버전 10.1.1i★ –i내 컴퓨터에서 실행
레지스트리 이름ai.kawacode/mcp

설치

개요

제작자가 쓴 설명(영어 원문)

Team-aware memory: intent, decisions, real-time conflicts for AI coding assistants.

PopNx MCP의 세 기둥

이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.

할 수 있는 일

이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.

  • 연결 방식: 내 컴퓨터에서 실행
  • 전송 방식: stdio
  • 카테고리: 검색 및 AI 기억

설치

쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.

설치하기 전에

  • 기본 점검: 1개 중 1개 통과
  • 내 컴퓨터에서 내 사용자 계정의 권한(파일, 네트워크, 앱)으로 실행돼요.
  • 레지스트리에 입력해야 할 키가 나와 있지 않아요.

필요한 것

  • npmNode.js 설치(npx 명령어용)

어떤 앱을 쓰세요?

위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.

Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요

{
  "mcpServers": {
    "kawacode": {
      "command": "npx",
      "args": [
        "-y",
        "@kawacode/mcp"
      ]
    }
  }
}

터미널에서 이 명령어를 실행하세요

claude mcp add kawacode -- npx -y @kawacode/mcp

Cursor에서 열기

또는 설정을 직접 복사하기

프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요

{
  "mcpServers": {
    "kawacode": {
      "command": "npx",
      "args": [
        "-y",
        "@kawacode/mcp"
      ]
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

VS Code에서 열기

또는 설정을 직접 복사하기

프로젝트의 .vscode/mcp.json에 붙여 넣으세요

{
  "servers": {
    "kawacode": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@kawacode/mcp"
      ]
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.

선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.

이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.

할 수 있는 일

내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.

기본 점검i

누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검

  • ✓ 통과

    제작자와 저장소 일치

    레지스트리 이름이 도메인 kawacode.ai 기준으로 확인되었어요(레지스트리가 도메인 소유를 확인해요)

  • … 아직 점검 안 함

    계속 관리되고 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • … 아직 점검 안 함

    라이선스 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • – 해당 없음

    엔드포인트 응답

    내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요

  • – 해당 없음

    OAuth로 로그인

    내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요

  • … 아직 점검 안 함

    도구 설명에 숨겨진 지시 없음

    내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요

검색 및 AI 기억 카테고리의 다른 서버와 비교i

  • 이 카테고리의 다른 서버 7241개 중 0%보다 스타가 많아요
  • 이 카테고리의 다른 서버 7241개 중 90%보다 최근에 레지스트리에 공개됐어요
  • 기본 점검 결과가 이 카테고리의 다른 서버 7241개 중 100%와 같거나 더 좋아요

레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.

자주 묻는 질문

Kawa Code, 안전한가요?

해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.

어떤 키나 코드가 필요한가요?

레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.

내 컴퓨터에서 실행되나요, 클라우드에서 실행되나요?

내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).

아직 관리되고 있나요?

GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(10.1.1)은 3일 전 레지스트리에 올라왔어요.

어떤 앱에서 쓸 수 있나요?

Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.

대신 쓸 수 있는 건 뭐가 있나요?

같은 카테고리에는: Context7, Codebase Memory, Exa

대안

같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.

카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i

Context7

제작자: upstash

Up-to-date docs for AI agents

컴퓨터 또는 클라우드★ 64,224MIT3일 전 업데이트
설치

Codebase Memory

제작자: DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

내 컴퓨터에서 실행★ 48,148MIT20일 전 업데이트
설치

Exa

제작자: exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

클라우드에서 실행★ 5,213MIT44일 전 업데이트
설치

제작자의 README

README 열기

제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.

Kawa Code MCP

Team-aware memory for AI coding assistants. Track intent, record decisions, and see when a teammate is editing the same code — in real time, before commit.

@kawacode/mcp is the official Model Context Protocol (MCP) server for Kawa Code. It lets Claude Code, Cursor, and any MCP-compatible AI assistant:

  • Remember what you're working on across sessions, branches, and machines — no more re-explaining the architecture every morning.
  • Surface team conflicts before they happen — know when a teammate is editing the same file or function in their working copy *right now*, before either of you commits.
  • Capture architectural decisions with their reasoning — future you (and future AI sessions) inherit the team's accumulated context instead of relitigating choices.
  • Link commits to intent automatically — every commit gets the *why* attached, not just the diff.

Prerequisites

Required
  • Node.js >= 18.0.0 — runtime for the MCP server
  • [Kawa Code](https://kawacode.ai) desktop app running — kawa.mcp is a thin MCP-to-IPC adapter; all git operations, storage, and API communication happen in Kawa Code
Optional (for history inference)
  • Anthropic API key — your own Claude API key, passed as a parameter to the inference tools
  • [GitHub CLI (`gh`)](https://cli.github.com/) — enables richer data tiers (PR descriptions, review comments, issue discussions). Without gh, tiers 2 and 4 are skipped automatically

Installation

Add the MCP in your AI configuration, for example on Claude Code:

claude mcp add -s user kawa-intents -- npx -y @kawacode/mcp

For Cursor AI, install the MCP with npm install -g @kawacode/mcp and add it to ~/.cursor/mcp.json.

{

"mcpServers": { "kawa-intents": { "command": "kawacode-mcp" } } }

Note that the MCP will not be automatically updated to future versions in this scenario. To upgrade to a newer release, run npm update -g @kawacode/mcp.

Manual Installation

For the project you want Kawa Code to run on, create a .mcp.json file in your project root (recommended for teams — commit it to git):

{

"mcpServers": { "kawa-intents": { "type": "stdio", "command": "npx", "args": ["-y", "@kawacode/mcp"] } } }

Usage

The MCP server works together with the Kawa Code application, Kawa Code IDE extensions, and AI code generators such as Cursor AI and Claude Code.

Pre-edit decision check (Claude Code hook) — retired

Retired 2026-08-14. Do not wire this up. Kawa Code no longer installs it, and the setup wizard no longer asks for it.

This hook fired before every Edit/Write and surfaced prior reasoning attached to the file being changed. It was retired because its retrieval could not reach the decisions that mattered: it read only the most recently updated 100 decisions per repository, and architectural constraints — precisely what it existed to surface — are written once and then age out of a recency window permanently. On one of our own repositories, 160 decisions were of the surfaced types and only 17 were still inside that window.

If you already installed it, nothing breaks. The kawacode-on-pre-edit binary still ships, and an existing entry in your settings.json keeps working. Kawa Code will not remove it for you — delete it yourself if you want it off:

"PreToolUse": [ { "matcher": "Edit|Write", "hooks": [ … ] } ]

Nothing is lost on team coordination. The live collision signal moved to the Stop hook some time ago, and that is now the only edit-level coordination surface. It reports teammates whose *in-progress, uncommitted* edits overlap the lines you touched this turn — conflict detection before a merge conflict can exist. See Team conflict detection.

Key Features

  • Real-time team conflict detection — see when a teammate is editing the same files or lines in their working copy, *before either of you commits*. Most version-control tooling shows you this after the merge conflict; Kawa shows you before. Kawa can also *judge* an overlap and apply the safe tier of merge for you — though that write only happens in an agent-owned worktree.
  • Cross-session AI memory — your AI assistant picks up where it left off across days, branches, and machines. No re-explaining the architecture every morning.
  • Decision history with reasoning — record forks, trade-offs, and abandoned approaches with their *why*. Future sessions and teammates inherit the context instead of re-deriving it.
  • Commit ↔ intent linkage — every commit is automatically associated with the intent that drove it. git log shows what changed; Kawa shows why.
  • Smart context retrieval — relevance-based loading; only what the current task needs.
  • Zero-knowledge encryption — code blocks encrypted client-side before sync. The Kawa cloud cannot decrypt your team's code.
  • Cross-platform — works with Claude Code, Cursor, and any MCP-compatible AI assistant.

Running several agents in parallel

Kawa Code is built for more than one worker on a repository at a time — that's what the conflict detection is *for*. If those workers are AI agents you're running yourself, give each one its own git worktree. Agents sharing a single checkout overwrite each other's edits with no conflict marker and no git history: nothing is committed between the two writes, so nothing notices.

Set up worktrees

In Claude Code, background sessions already require a worktree — worktree.bgIsolation defaults to "worktree", which blocks edits to the main checkout until the session enters one. You only need to touch it if a project has explicitly opted out with "none". Subagents take isolation: "worktree" per spawn.

Two settings are worth tuning, because the defaults surprise people:

{

"worktree": { "baseRef": "head", "symlinkDirectories": ["node_modules", "target"] } }

  • `baseRef` — defaults to "fresh", which branches from origin/ . If you work on unpushed commits, set "head" to branch from your local HEAD instead. Either way this is a *commit* boundary: uncommitted working-tree changes don't travel into a new worktree, so land your work before spawning agents that need it.
  • `symlinkDirectories` — nothing is symlinked unless you say so, so every worktree gets its own copy of whatever you leave out. Symlink *dependency* directories freely: node_modules is the same content for every worktree, and sharing it costs nothing. Do not symlink compiled-language build output — target/, build/, obj/. Those tools name artifacts deterministically from the crate/module and its inputs, *without* encoding which checkout they came from, so two worktrees building into one directory write the same filenames and silently overwrite each other. The symptom is the dangerous part: your suite goes green while running another checkout's binaries. Only a test that resolves a path baked in at compile time (Rust's env!("CARGO_MANIFEST_DIR"), include_str!, or an equivalent) will notice; everything else passes. If a suite ever looks suspiciously green after another checkout built in the same place, clean the build directory and re-run before believing it.

Because compiled build directories can't be shared, they multiply — one per worktree, each growing independently, and they get large enough to matter (a mature Rust target/ reaches hundreds of gigabytes). Two things keep that affordable, and they solve different halves:

  • Speed — a compiler cache such as sccache is safe across worktrees precisely because it caches *results* keyed by input hash rather than sharing an output directory.
  • Disk — prune periodically. For Rust, cargo-sweep removes stale artifacts by age or to a size cap; wire it into whatever cadence fits your setup — after merging a worktree back is a natural trigger. One caveat worth knowing before you rely on it: sweeping only reclaims artifacts the build tool still tracks. If that index has been lost, the leftovers are orphaned and a sweep reports nothing to do no matter the flags — a full clean is the only thing that reclaims them.
Keeping agents from colliding

Isolation alone would just give you several agents doing overlapping work in private. Kawa's job is the coordination on top.

Each agent session gets its own identity, and intents are tracked per session — so several intents can be active on one repository at once, each with its own current focus, without a lock and without agents clobbering each other's context. From there the normal machinery applies across agents exactly as it does across teammates: get_relevant_context surfaces what the *other* agents have already decided, create_and_activate_intent hands the user a decision in Kawa Code when new work overlaps something already in flight, and the Stop hook reports, once per turn, where another agent's live edits intersect yours.

The practical result: your agents inherit each other's decisions instead of re-deriving them, and you find out about overlapping work while it's still cheap to redirect — not at merge time.

Auto-resolution requires a worktree

Kawa can do more than *report* an overlap — arbiter_resolve judges each one, and arbiter_apply will write the safe tier of merge for you. That write is deliberately gated:

arbiter_apply writes only in an agent-owned worktree. On a human checkout — or when a peer holds the file-set lock — it stays suggest-only.

This is the sharpest practical reason to put agents in worktrees. Run them on a shared checkout and auto-resolution silently never engages; you get the conflict surfaced and nothing else, with no error to tell you a capability was switched off. The guardrail is intentional — Kawa won't rewrite a human's working tree underneath them — but it does mean the setup decides whether half the feature is available.

When an overlap is waiting on you

When an agent asks to start work that overlaps an intent already in flight, the agent doesn't get to decide. Kawa Code parks the request and asks you, in the Orchestration panel: create_and_activate_intent returns pending_approval with a pendingId, and the agent re-checks that id as it goes.

A parked overlap is not a stop. Nothing in Kawa Code halts an agent mid-task, and nothing is meant to — a refusal that froze the session would strand it for as long as you were away, and by the time you read the card the edits are usually already on disk. So the agent tells you the card is waiting and carries on with whatever doesn't depend on the intent existing. Cancelling behaves the same way: it withholds the intent and *asks* the agent to stop, so the card reports how many turns that session has taken since you cancelled rather than pretending the work was undone.

Can't see the card?

Check the panel's scope first — this is the usual cause, not expiry. Orchestration reads across repositories by default, but scoped to the current project it lists only cards for the repository you have focused, and the agent that parked the request is often working in a different one. Widen the scope, or focus that repository.

Lapsing after 24 hours — the card waits, the agent doesn't

A parked request has a 24-hour window, but the window bounds how long the agent waits, not how long you have:

whenthe agentyour card
within 24hre-checks the pendingId as it worksin the panel, marked needs your decision
after 24htold the request lapsed, and to ask againstill in the panel, marked Lapsed — and still answerable

**Expiry marks a request stale; it does not

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