Kawa Code MCP
Team-aware memory for AI coding assistants that tracks intent, records decisions, and detects real-time conflicts before commit.
README
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). Withoutgh, 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)
Optional. When the agent is about to edit code that has prior recorded reasoning attached (an overlapping intent's blocks, or a constraint with the file in relatedFiles), the hook surfaces it before the Edit fires. Recommendation maps to action: silent (proceed), advisory context injected (review), or blocked with stderr message (investigate-upstream).
Wire it as a Claude Code PreToolUse hook in your ~/.claude/settings.json or project .claude/settings.json:
{
"hooks": {
"PreToolUse": [
{
"matcher": "Edit|Write",
"hooks": [
{ "type": "command", "command": "npx -y -p @kawacode/mcp kawacode-on-pre-edit" }
]
}
]
}
}
Override paths when blocked:
- Persistent (recommended): record a fork decision that supersedes the existing one and retry the Edit.
record_decision(type: "fork", supersedes: ["<surfaced-decision-id>"], rationale: "...") - One-off escape hatch: add
force: trueto the Edit tool args. The hook acks the surfaced decisions in the session cache and allows the edit. Cache resets when the Kawa Code daemon restarts.
Disable the hook for a session with KAWA_PRE_EDIT_CHECK=off.
Local telemetry (logs)
Every pre-edit check fire (and force-override) appends a JSON line to a daily-rotated file at ~/.kawa-code/logs/pre-edit-decision-check-YYYY-MM-DD.jsonl. Logs are local only — nothing leaves your machine. The defaults keep the last 30 days, capped at 100 MB total (oldest files dropped first).
Each line records what fired, why, and what was filtered out — useful for tuning the recommendation thresholds and spotting false positives over time.
Disable telemetry with KAWA_PRE_EDIT_TELEMETRY=off.
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.
- 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 logshows 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.
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:
- Build the project:
npm run build - Run the server:
npm start - The server communicates via stdio (standard input/output)
- You can send MCP protocol messages via stdin to test tool functionality
Development Tips
- Use
npm run devto 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.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.