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SurajKGoyal/amnesic

SurajKGoyal/amnesic

Persistent schema memory for Postgr
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add amnesic -- npx -y amnesic
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
4 ★ · SurajKGoyal/amnesic · 取自 GitHub 搜索 API · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
评分构成
综合分 703 · 4 ★ · 7 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 SurajKGoyal/amnesic;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

amnesic — the MCP server with the most ironic name in the registry

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

**Your database's institutional memory, as an MCP server. The name is ironic — it remembers everything.**
*"The MCP server with the most ironic name in the registry. It's anything but amnesic — it remembers your database so your AI doesn't have to."*
Most database MCP servers are **query executors**: they connect, introspect, run SQL, and forget. amnesic is a **semantic memory** — it accumulates what your schema *means* (what status = 3 is, which columns are really foreign keys, what that legacy table is for) and hands it to every future session automatically. Think data catalog, minus the platform, the ingestion pipeline, and the invoice. Where amnesic fits ↓
**Works with** Claude Code · Claude Desktop · Cursor · VS Code · Cline · Windsurf — any MCP-compatible client.
**Available on** Official MCP Registry · Claude Code plugin marketplace
👋 **Using amnesic?** Say hi in the adopters thread — download counts can't tell me what's actually being used, and it directly shapes what gets built next.
> 🔒 **Read-only by design.** amnesic refuses to execute INSERT, UPDATE, DELETE, DROP, TRUNCATE, ALTER, CREATE, EXEC, MERGE, GRANT, REVOKE — and any write statement smuggled inside a WITH CTE. Two layers of defense: static SQL analysis rejects the statement before connecting, **and** every query runs inside a transaction that is immediately rolled back. Safe to point at prod. Details ↓
---
The problem
Every session with an AI starts cold. You spend the first few minutes re-explaining what tables exist, what a status column value of 3 means, which FK connects orders to users. Then the session ends, and you do it all over again tomorrow.
**amnesic fixes this.** It gives your AI a persistent SQLite knowledge store — one per database — that survives across sessions. Annotate a status enum once; every future session sees those labels automatically. Discover FK relationships once; every future JOIN query uses that graph.
The knowledge is also **portable and outlives your access to the database**. When you rotate off a project, amnesic export hands the next developer everything you taught it — years of "oh, that column actually means…" that would otherwise leave with you.
---
Where amnesic fits
The database MCP ecosystem splits into two camps, and amnesic is deliberately in neither.
**Query executors** — DBHub, Postgres MCP Pro, Google's MCP Toolbox, and the vendor servers (Supabase, Neon). They introspect live, run SQL, and some go deep on performance — Postgres MCP Pro does genuine index tuning and PgHero-style health checks. They are excellent at this. They are also **stateless**: every session re-learns your schema from scratch, and nothing they return can tell you what a column *means*, because the database doesn't know either.
**Enterprise catalogs** — DataHub, Atlan, Cube, AtScale. These *do* hold semantic context: glossaries, column descriptions, ownership, lineage. They're also a platform commitment — metadata ingestion, a service to run, usually a paid tier. Worth it at company scale; wildly disproportionate for one developer who needs to remember what six status codes mean in a legacy MSSQL database nobody will ever onboard to a catalog.
**amnesic is the third thing**: catalog-grade semantic memory at query-executor setup cost. pipx install, one TOML file, a local SQLite file per database. No platform, no ingestion, no server to run.
Honest comparison
| | amnesic | Query executors | Enterprise catalogs |
|---|---|---|---|
| **Semantic context** (what a value *means*) | ✅ persistent, yours | ❌ none | ✅ platform-managed |
| **Survives across sessions** | ✅ | ❌ | ✅ |
| **Portable / outlives DB access** | ✅ export/import | ❌ | ⚠️ platform-bound |
| **Setup cost** | one command | one command | ingestion pipeline |
| **Live schema freshness** | ⚠️ cached, manual refresh | ✅ always live | ⚠️ ingestion lag |
| **Execution plans / index tuning** | ❌ | ✅ (Postgres MCP Pro) | ❌ |
| **Lineage / ownership / governance** | ❌ | ❌ | ✅ |
| **Works on legacy schemas with no FK constraints** | ✅ annotate them yourself | ❌ nothing to introspect | ⚠️ needs ingestion |
**Use a query executor instead of amnesic if** you want execution plans, index recommendations, or database health diagnostics — that's not amnesic's job and adding it would make it a worse version of a tool that already exists.
来源
awesome · https://github.com/SurajKGoyal/amnesic
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