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 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) — enables richer data tiers (PR descriptions, review comments, issue discussions). Without gh, tiers 2 and 4 are skipped automatically

Related MCP server: Projectmem

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/<default-branch>. 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 reports a conflict when new work overlaps something already in flight, and the pre-edit check fires on reasoning any of them recorded.

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.

Handing off work to a teammate (no session export)

Because the reasoning behind your work — your intents and recorded decisions — lives in Kawa Code rather than in the chat log, a teammate can pick up where you left off from a single prompt. No transcript sharing, no session restore.

1. Commit or push your code first. A handoff prompt carries your reasoning, not your uncommitted working tree — so land the code (or publish the pre-commit diff) before you hand off, otherwise your teammate inherits the decisions without the diff that goes with them.

2. Grab the intent id. The id of the intent you were working under — your agent can read it back with check_active_intent, or you can find it in the Kawa Code app.

3. Hand over a one-line prompt, e.g. Follow up on intent <intent-id>: <what's left to do>.

4. Your teammate pastes it into a fresh session. Their agent calls resume_intent(<id>) — one call that adopts the intent as their current focus and loads its recorded decisions — resuming the thread with full context, even though it never saw your chat.

What transfers: the intent, its decisions, and (once committed) its code. What doesn't: your chat transcript and any session-local state. An acknowledgment you made to a pre-edit block is your judgment in your session, so your teammate re-evaluates it rather than inheriting it — which is what you want.

Teams: to make the handoff seamless, add one line to your shared CLAUDE.md so the agent always treats a follow-up prompt as resuming the named intent instead of opening a new one:

When a prompt says "follow up on intent <id>" (or similar), call resume_intent(<id>) to adopt that intent and load its decisions — do not create a new intent for it.

Migrating or rewriting a codebase? Transplant its decisions

When you port a codebase to a new language or rebuild it in a fresh repository, the code moves — but the reasoning usually doesn't. The source repo's decision history knows why retired approaches were retired, which constraints are load-bearing, and where the security landmines are. With Kawa Code, that history becomes a first-class migration input.

Decisions are scoped per repository, so the new repo won't surface the old repo's history automatically. Transplant them slice by slice as you port — this is the recall-transplant workflow:

1. Recall before porting each slice. Call get_relevant_context against the source repo with a description of the subsystem you're about to port (name its key files). This surfaces the forks, constraints, trade-offs, and discoveries that shaped it.

2. Expand what matters. Recall returns summaries — call get_decision_detail on the load-bearing hits for the full rationale and consequences.

3. Classify: stack-portable vs stack-bound. Domain truths port: protocol contracts, cost/scale rationale, security discoveries, "we tried X and retired it" warnings. Mechanics of the old stack don't: build-tooling quirks, runtime workarounds, library-specific fixes. Only the portable ones move.

4. Re-record the portable ones in the target repo with record_decision, citing provenance in the summary or rationale (e.g. [transplanted from <source-repo> <decision-id>]). Merge decisions that form one lineage into a single record.

5. Let the transplants shape the port and its tests. A transplanted durability rationale should become a test that proves the property survived the rewrite; a retired-approach warning should stop the new stack from reintroducing it.

The payoff compounds: the port doesn't re-litigate settled arguments or faithfully reproduce old bugs, negative knowledge survives even though the code that motivated it was deleted long ago, and at cutover the new repo starts with a curated decision corpus instead of an empty one.

The CLAUDE.md template ships a compact version of this workflow, so agents set up through the Kawa Code welcome flow follow it automatically.

Occasional operations

Most Kawa tools run every turn — check the active intent, recall context, record a decision. The operations below are different: you run them rarely, sometimes once per repository. They cost real time and money, and they are not part of the per-turn loop.

Seeding a repo from its git history — infer_history

A brand-new Kawa repo knows nothing about work that predates it. infer_history mines the existing commit history into intents and decisions, so recall has something to draw on from day one. Run it once when you connect a repo with meaningful history; after that it extends incrementally.

It is agent-invoked — ask your assistant, e.g. "Run infer_history with max 3000 commits". There is no button for it in the Kawa Code app.

Always estimate first. The tool defaults to estimateOnly: true, which returns a token/cost preview without running anything. Look at the number, then re-run with estimateOnly: false to actually start. A run is asynchronous — it returns immediately and reports progress in the Kawa Code app — and resumes from where it stopped if interrupted.

The re-run guard. If the repo already has intents and the run can't cleanly resume (missing or unreachable cursor), or HEAD isn't on the default branch, the call stops and returns needsDecision instead of running. That's deliberate: re-running blind duplicates intents. Read the reason, and only pass force: true if it genuinely applies. Prefer running on main/master; force exists for the deliberate feature-branch case.

GitHub and GitLab are both supported; the forge is detected from the remote origin.

Decision evolution — automatic, no call needed

Curating decisions into an evolution graph is phase 5 of infer_history, run automatically once the analysis completes. There is no separate step and nothing to invoke.

Earlier versions exposed an evolve_decisions tool. It has been removed: it required a stories array that only ever existed inside the pipeline's own memory, so no assistant could construct a valid call. Nothing is lost — the curation still runs, as part of infer_history.

Updating the feature catalog — use the Features panel

Features group a repo's intents into a browsable catalog. Rebuild it from the Features panel in the Kawa Code app:

• Update features — additive. Folds intents that aren't in the catalog yet into the existing features. This is the everyday action.

• Rebuild — cold rebuild from scratch, keeping locked features. Use when the catalog has drifted badly.

Progress shows in the app, and the catalog also extends automatically after an infer_history run.

Earlier versions exposed an update_features MCP tool that sent the same request as the Update features button. It has been removed — one button and one tool doing the identical thing meant every session paid for a tool schema it never needed. Press the button instead.

Development

# Watch mode (auto-rebuild on file changes)
npm run dev

# Build TypeScript to JavaScript
npm run build

# Clean build artifacts
npm run clean

# Run the MCP server directly
npm start

Testing the MCP Server

To test the MCP server without integrating it into an AI assistant:

1. Build the project: npm run build

2. Run the server: npm start

3. The server communicates via stdio (standard input/output)

4. You can send MCP protocol messages via stdin to test tool functionality

Development Tips

• Use npm run dev to auto-rebuild during development

• Check stderr for server logs (stdout is reserved for MCP protocol)

• Ensure Kawa Code is running before testing

Architecture

Claude Code / Cursor AI
    ↓ MCP Protocol (stdio)
kawa.mcp (this server)
    ↓ Huginn IPC (Unix socket / Named pipe)
Kawa Code Desktop App
    └─ HTTP Client
        ↓ REST + SSE
    Kawa API (cloud)
        └─ Team sync & zero-knowledge encryption

Contributing

Contributions are welcome. Please read CONTRIBUTING.md and CLA.md.

License

This project is source-available under the Kawa Code Source Available License.

You may run and modify the software for personal or internal use.

See LICENSE for details.