Zenrei
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@ZenreiCheck this design proposal against past decisions"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Zenrei(前例)
"That proposal? There's a precedent." — Decision memory for AI-driven development.
AI agents don't remember past discussions. They keep re-proposing designs you rejected weeks ago. Zenrei records your decisions — accepted, rejected, deferred — as Markdown in your repos, and serves them to every AI agent (Claude Code / Cursor / CI) over MCP. When an agent re-proposes a rejected design, check_proposal stops it.
git-native — decisions live in your git. Zenrei indexes and serves; it never owns your data
Humans decide — agents can only file drafts (
pending); only a human can accept or rejectDeterministic & light — no LLM calls, no API key, works offline (Japanese-aware bigram BM25). With 1,000 decisions, responses stay ~1,800 chars / 44ms — your prompts never bloat
🌐 How it works: https://zenrei.karakurio.com ・ Operations guide: https://zenrei.karakurio.com/guide
Quick start
claude mcp add zenrei --scope user -- npx -y zenrei --root /path/to/repo1 --root /path/to/repo2For English tool responses, append --lang en (default is Japanese; or set ZENREI_LANG=en).
Add three lines to each repo's CLAUDE.md (agent instructions):
## Decision memory (zenrei)
- At session start, call get_context (scope: this repo) to load decided matters
- Before proposing designs or policies, call check_proposal
- File new decision points with record_decision (humans approve)Decision file format: docs/decision-format.en.md(日本語: docs/decision-format.md)
Related MCP server: OKF Knowledge MCP
Tools (fixed at five)
tool | role |
| Match a proposal against past decisions — "rejected on 2026-07-08, because …" |
| Search by keyword / status / scope / date range |
| File a decision draft ( |
| List drafts and deferred decisions |
| A digest of relevant decisions for session start |
Repository layout
src/— local MCP server (stdio)packages/core/— parsing / matching / formattingpackages/cli/— thezenreinpm packagedocs/— decision format spec (EN / JA)
The hosted version (GitHub App, cross-repo timeline, approval UI, PR gate) is operated separately: https://zenrei.karakurio.com
Development
npm install
npm run build
npm test日本語
Zenrei(前例)は、AI駆動開発のための意思決定メモリです。採用・却下・保留の決定をリポジトリ内のMarkdown(decisions/*.md)で管理し、MCP経由で全AIエージェントに配ります。エージェントが却下済みの設計を蒸し返したら check_proposal が止めます。
git-native: 決定はあなたのgitの中。データを人質に取りません
決定するのは人間: AIが起票できるのは承認待ち(pending)まで
決定論的照合: LLM不使用・APIキー不要・オフライン動作。決定が増えてもプロンプトは太りません
導入は上のQuick startのとおり。仕組み: https://zenrei.karakurio.com / 使い方: https://zenrei.karakurio.com/guide / 決定フォーマット仕様: docs/decision-format.md
License
MIT
This server cannot be deployed
Maintenance
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Give your AI agent persistent, governed memory for every project. At task start it recalls the approved decisions, conventions, risks and architecture (semantic search, ranked by importance); at close it proposes what was learned as typed memories that you review and approve — governance, not a notes dump. Agents propose, humans govern: edits go back to pending and deletion is human-only by design. Connect Claude Code, Cursor, Claude Desktop or any MCP client in two minutes with just your API key — hosted (nothing to install) or locally via `uvx solucortex-mcp`. Built by SoluAI and dogfooded daily: SoluCortex is developed using its own living memory.
Long-term memory for AI coding agents: durable project facts, recalled by every MCP client.
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