Anumana

Name: Anumana
Author: sinhaKAN-ra

作者：sinhaKAN-ra版本 0.2.1i★ –i在你的电脑上运行

注册名称io.github.sinhaKAN-ra/anumana

安装

概览

作者提供的说明（英文原文）

Predict query cost, explain the plan, and rewrite it before you run it — 12 DB engines.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数：意见、测量和人气是不同的东西。

用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
我们的基础检查i1 项中通过 1 项依据公开信息检查；尚未扫描代码
使用情况i非常新↓ 28/周 · ★ –

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

连接方式: 在你的电脑上运行
传输方式: stdio
分类: 其他
你需要填写：ANUMANA_DSN, ANUMANA_TARGETS

安装

选择你使用的 AI 应用，然后复制设置。

安装之前

基础检查：1 项中通过 1 项
在你的电脑上运行，拥有你的用户账户的权限（文件、网络、应用）。
需要你自己填写： ANUMANA_DSN, ANUMANA_TARGETS, ANUMANA_POLICIES

标为机密的值是你账户的钥匙。千万不要分享给别人，也不要粘贴到聊天里。

你需要

PyPI已安装 Python 的 uv（用于 uvx 命令）

你用的是哪个应用？

ClaudeClaude CodeCursorVS CodeChatGPT

在上方选择你的应用。我们会记住它，下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config，把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "anumana": {
      "command": "uvx",
      "args": [
        "anumana-mcp"
      ],
      "env": {
        "ANUMANA_DSN": "your-value",
        "ANUMANA_TARGETS": "your-value",
        "ANUMANA_POLICIES": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add anumana --env ANUMANA_DSN=your-value --env ANUMANA_TARGETS=your-value --env ANUMANA_POLICIES=your-value -- uvx anumana-mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json，或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "anumana": {
      "command": "uvx",
      "args": [
        "anumana-mcp"
      ],
      "env": {
        "ANUMANA_DSN": "your-value",
        "ANUMANA_TARGETS": "your-value",
        "ANUMANA_POLICIES": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "anumana": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "anumana-mcp"
      ],
      "env": {
        "ANUMANA_DSN": "your-value",
        "ANUMANA_TARGETS": "your-value",
        "ANUMANA_POLICIES": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

这个服务器在你的电脑上运行，而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上，无需账户。

需要你填写的值

ANUMANA_DSN 机密 env
Read-only connection string for the primary target database (e.g. postgresql://readonly@host:5432/db). Optional if ANUMANA_TARGETS is used.
ANUMANA_TARGETS 机密 env
JSON array of named targets for a multi-database setup, each with name, engine, and connection string.
ANUMANA_POLICIES env
JSON array of operator enforcement policies (block/warn/allow rules by risk tier or flag). Optional; open by default.

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。

它能做什么

它在你的电脑上运行；安装后，工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月10日

✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 sinhaKAN-ra 验证，该账户拥有此仓库
… 尚未检查
仍在维护
我们还没有从 GitHub 读取这个仓库
… 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
– 不适用
端点有响应
它在你的电脑上运行，没有互联网端点
– 不适用
使用 OAuth 登录
在你的电脑上运行，改用本地设置
… 尚未检查
工具描述中没有隐藏指令
它在你的电脑上运行；我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

星标数多于此分类中其他 19018 个服务器的 0%
发布到注册中心的时间比此分类中其他 19018 个服务器的 56% 更新
基础检查结果等于或优于此分类中其他 19018 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

常见问题

Anumana 安全吗？

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前，请先看看这个服务器要求哪些权限，并使用只具备所需权限的密钥。

它需要哪些密钥或代码？

你需要填写：ANUMANA_DSN, ANUMANA_TARGETS

它在我的电脑上运行还是在云端？

它在你的电脑上运行。你的 AI 应用会在需要时启动它，数据不会经过作者的服务器（除非它自己调用在线服务）。

它还在维护吗？

GitHub 仓库最后更新于–，最新版本（0.2.1）于36天前进入注册中心。

哪些应用可以使用它？

支持 MCP 的应用，例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它？

同一分类中有：Spec Driven Development, Remote Desktop Commander, Google Jobs

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：↓ 每周下载量i★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

作者：formulahendry起步阶段↓ 66/周★ 44014个月前更新

在你的电脑上运行

安装

Remote Desktop Commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

作者：desktop-commander正在增长★ 211今天更新

在云端运行✓ desktopcommander.app

安装

Google Jobs

Google Jobs listings (title, company, salary, description) + AI-training job boards.

作者：wulfcare起步阶段今天更新

在云端运行

安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Anumana

Know what your query will cost — before you run it. *Inference-grade foresight for every query your AI writes.*

Anumana is an MCP server that catches the costly query your AI coding agent just wrote — *before* it runs or reaches a PR. It rides inside Claude, Cursor, Windsurf, Codex, Kiro, or any MCP-compatible agent, reads your real schema via EXPLAIN (never EXPLAIN ANALYZE), and tells you — in plain English — how the query behaves and whether it'll hurt.

Its scope is the queries AI agents actually generate: text-to-SQL today, and RAG / vector search (pgvector) alongside it — because an agent writing a similarity search has no idea it just triggered a brute-force scan over every embedding. Anumana is the feedback loop the agent is missing.

It is not another NL→SQL tool and not a DB-health dashboard. It does one job: stop AI-written database code from silently rotting production.

What it does (the features)

Tool	What it answers
`preflight_query`	"Will this SQL query be costly?" — risk tier (cheap/moderate/expensive/dangerous), rows scanned vs returned, scan strategy, and overhead flags. Without running it.
`preflight_vector_search`	"Will this RAG similarity search be costly?" — catches the vector traps a plain SQL check misses: brute-force scan with no HNSW/IVFFlat index, `top_k` too large, unbounded search, metadata-filter/ANN recall loss.
`rewrite_query`	"Make it cheaper." — a verified equivalent rewrite with before/after planner cost, plus index suggestions gated on selectivity (won't tell you to index a column when the filter matches most of the table). `engine="pgvector"` suggests an HNSW index.
`explain_query_working`	"How does this run?" — two layers: the logical gather order (FROM → WHERE → GROUP BY → HAVING → SELECT → ORDER BY → LIMIT) and the actual physical plan for your schema, step by step.
`preflight_schema_only`	"I haven't given you DB creds yet." — static analysis against pasted `CREATE TABLE` DDL, no connection. Offline, zero-trust front door.

Engines (12, across 7 paradigms): Postgres and SQLite are live-tested;

MySQL, pgvector, MongoDB, DynamoDB, FalkorDB, Cassandra, Redshift, BigQuery,

Snowflake and ClickHouse ship as offline-verified, untested adapters that

are promoted to live one at a time. Full matrix + cost signals in

SUPPORTED_ENGINES.md. The adapter interface is in

DESIGN.md.

The one honest rule

Postgres planner cost is unitless — not milliseconds (docs). Anumana never fakes a ~3.2s number. It reports rows scanned, scan strategy, a risk tier, overhead flags, and the cost-delta of a rewrite — all defensible, nothing invented. Every estimate carries an accuracy tier (UPPER_BOUND live, HEURISTIC schema-only).

Install

pip install anumana-mcp          # once published to PyPI

or from source:

pip install -e .

Then point your agent at it. The user installs it; the agent discovers the tools automatically on connect via the MCP tools/list handshake — there is no store to publish into.

Claude Desktop / Cursor / Windsurf / Kiro — `mcpServers` config block

"mcpServers": { "anumana": { "command": "uvx", "args": ["anumana-mcp"], "env": { "ANUMANA_DSN": "postgres://readonly@localhost:5432/mydb" } } } }

Use a **read-only** Postgres role. Anumana only ever `EXPLAIN`s, but read-only is

defence in depth. Omit ANUMANA_DSN to run in schema-only mode (DDL in, no DB).

Try it with no database (30 seconds)

python3 src/demo.py          # runs the engine on a canned plan, zero deps

Test against a real Postgres

# a throwaway table, then:

ANUMANA_DSN=postgres://localhost/mydb anumana-mcp

See `src/live_test.py` for a `psql`-backed harness that proves the real

cost-delta and the selectivity gate on live data.

What's deliberately NOT here

No run_query (we never execute your SQL), no NL→SQL (the agent already does that), no DB-health reports, no dollar-billing. Staying narrow is the strategy.

License

MIT — see LICENSE.

Community & contact

Contributions welcome — see CONTRIBUTING.md and the Code of Conduct. Adding a database engine is the highest- leverage contribution; the adapter contract is small (SUPPORTED_ENGINES.md).

Bugs / ideas: open a GitHub issue.
Security: see SECURITY.md — report privately.
Maintainer: nomore.report@gmail.com

Anumana

概览

PopNx MCP 的三大支柱

它能帮你做什么

安装

安装之前

需要你填写的值

它能做什么

基础检查i

作者与仓库一致

仍在维护

有许可证

端点有响应

使用 OAuth 登录

工具描述中没有隐藏指令

与“其他”中的其他服务器比较i

常见问题

替代选择

Spec Driven Development

Remote Desktop Commander

Google Jobs

作者的 README

Anumana

What it does (the features)

The one honest rule

Install

or from source:

Claude Desktop / Cursor / Windsurf / Kiro — mcpServers config block

Try it with no database (30 seconds)

Test against a real Postgres

What's deliberately NOT here

License

Community & contact

Claude Desktop / Cursor / Windsurf / Kiro — `mcpServers` config block