sqlew
Stores architectural decisions in a SQL database for persistent AI agent memory, enabling cross-session continuity and duplicate detection.
README
sqlew

Design decisions, remembered by SQL — an MCP server for AI agents
What is sqlew?
The Problem
Every AI coding session starts from scratch. Your agent doesn't remember that you chose PostgreSQL over MongoDB last week, or that the team agreed on a specific API versioning strategy. Without persistent memory, agents repeat mistakes, contradict earlier decisions, and waste tokens re-discovering context.
The Solution
sqlew stores your architectural decisions in a structured SQL database. When a new session starts, the AI agent queries past decisions in milliseconds — not by reading through scattered Markdown files, but through efficient SQL lookups with metadata, tags, and similarity detection.
┌─────────────────────────────────────────────────────────────┐
│ Before sqlew │ After sqlew │
│───────────────────────────────│─────────────────────────────│
│ Session 1: "Use PostgreSQL" │ Session 1: "Use PostgreSQL"│
│ Session 2: "Use MongoDB?" │ → decision recorded │
│ Session 3: "Use PostgreSQL" │ Session 2: query → got it │
│ (same debate, every time) │ Session 3: query → got it │
│ │ (instant recall) │
└─────────────────────────────────────────────────────────────┘
sqlew is built on the Model Context Protocol (MCP), so it works with any MCP-compatible AI coding tool.
This software does not send any data to external networks. We NEVER collect any data or usage statistics.
Quick Start
1. Install
npm install -g sqlew
2. Setup
Choose the setup that matches your environment:
Claude Code (Plugin)
claude plugin marketplace add sqlew-io/sqlew-plugin
claude plugin install sqlew
The plugin automatically configures MCP server, Skills (Plan Mode guidance), and Hooks (automatic decision capture).
Codex CLI (Plugin)
codex plugin marketplace add sqlew-io/sqlew-plugin
codex plugin install sqlew --source sqlew-plugin
After install, open /hooks in Codex and trust the bundled sqlew hooks. Enable Plan Mode with collaboration_modes = true under [features] in your Codex config. The plugin configures MCP server, Skills (plan mode guidance), and Hooks (plan enforcement, PR ADR guard, decision extraction). See Hooks Guide for caveats (do not duplicate skills in ~/.codex/skills/ or add [mcp_servers.sqlew] to config.toml).
Grok Build (Plugin)
npm install -g sqlew
grok plugin install sqlew-io/sqlew-plugin --trust
grok plugin update
The plugin configures MCP server, Skills (plan mode guidance), and Hooks (automatic decision capture on exit_plan_mode). See Hooks Guide for setup details and caveats (do not duplicate hooks in ~/.grok/hooks/ or config.toml).
Manual
Add to .mcp.json in your project root:
{
"mcpServers": {
"sqlew": {
"command": "sqlew"
}
}
}
The database (~/.config/sqlew/sqlew-shared.db) and config are auto-created on first run. See Shared Database for details.
3. Just use Plan Mode!
That's it. Every time you create a plan and get user approval, your architectural decisions are automatically recorded.
No special commands needed — just plan your work normally, and sqlew captures the decisions in the background.
Features
- Structured Records — Decisions stored as relational data with metadata, tags, layers, and version history
- Fast Queries — 2-50ms retrieval via SQL, even with thousands of decisions
- Duplicate Detection — Three-tier similarity scoring (0-100) prevents redundant decisions
- Constraint Tracking — Architectural rules and principles as first-class entities
- Auto-Capture — Hooks automatically record decisions from Plan Mode (Claude Code, Codex, and Grok Build via sqlew-plugin)
- Multi-Database — SQLite (default), PostgreSQL, MySQL/MariaDB, or Cloud
- Git Worktree Ready — Each worktree shares the same context database
For Teams (sqlew.io)
Connect to sqlew.io for team-shared decisions:
Step 1: Get your API key
Visit sqlew.io and save your API key:
# ~/.config/sqlew/.sqlew.env (shared across all projects)
SQLEW_API_KEY=your-api-key
Step 2: Configure each project
# .sqlew/config.toml
[database]
type = "cloud"
[project]
name = "your-project-name"
Benefits:
- All team members share the same decision database
- Works seamlessly with Git worktree workflows
- No local database setup required
Performance
| Metric | Value |
|---|---|
| Query speed | 2-50ms |
| Concurrent agents | 5+ simultaneous |
| Storage efficiency | ~140 bytes/decision |
| Token savings | 60-75% vs Markdown ADRs |
Use Cases
- Architecture Evolution — Document major decisions with full context and alternatives considered
- Pattern Standardization — Establish coding patterns as constraints, enforce via AI code generation
- Cross-Session Continuity — AI maintains context across days/weeks without re-reading docs
- Multi-Agent Coordination — Multiple AI agents share architectural understanding
- Onboarding Acceleration — New AI sessions instantly understand project history
Documentation
| Guide | Description |
|---|---|
| ADR Concepts | Architecture Decision Records explained |
| Configuration | Config file setup, database options |
| Hooks Guide | Claude Code, Codex, and Grok Build integration |
| Cross Database | Multi-database support |
| CLI Usage | Database migration, export/import |
Upgrade Guides
- Migrating to SaaS — Export local data to sqlew.io cloud
MCP Tools
7 action-based tools: decision, constraint, suggest, help, example, use_case, queue
All tools support action: "help" for documentation.
Support
Support development via GitHub Sponsors.
Version
Current version: 5.2.0
See CHANGELOG.md for release history.
What's New in v5.2.0:
- Grok Build support — Plan-to-ADR via sqlew-plugin (
grok plugin install sqlew-io/sqlew-plugin --trust) - Grok plan.md injection — Decision/Constraint template appended on
enter_plan_mode - Hook normalization — Single CLI hook handlers work under both Claude Code and Grok Build
License
Apache License 2.0 — Free for commercial and personal use. See LICENSE for details.
Links
Built with MCP SDK, better-sqlite3, and TypeScript.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。