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Kawa Code

by kawacode-aiversion 10.1.1i★ –iRuns on your computer
Registry nameai.kawacode/mcp

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

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

Run this in your terminal

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

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified against the domain kawacode.ai (the registry checks domain ownership)

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

  • More stars than 0% of the other 7254 servers in this category
  • Published to the registry more recently than 90% of the other 7254 servers in this category
  • Basic checks equal to or better than 100% of the other 7254 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Kawa Code safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (10.1.1) reached the registry 4 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated today
Install

Codebase Memory

by DeusData

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

Runs on your computer★ 48,148MITUpdated 20 days ago
Install

Exa

by exa-labs

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

Runs in the cloud★ 5,213MITUpdated last month
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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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