mcpbeat

stagenth · 数据工具箱 MCP Server

com.stagenth/data-kit
answering

stagenth · 数据工具箱 is answering right now. Last checked 6 min ago. It exposes 6 tools.

Query, join, profile, clean and convert CSV/JSON/Parquet with server-side DuckDB over MCP.

Uptime history 40 hours of history · worst hour 75%
40 hours agonow
100.0%
Uptime 24h
91 of 91 checks
6
Tools
read from the server
1211 ms
Response time
average over 24h
open, no key
Access
streamable-http

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 6 min ago.

run in your terminal
claude mcp add data-kit --transport http https://stagenth.com/mcp/data-kit/
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "data-kit": {
      "url": "https://stagenth.com/mcp/data-kit/"
    }
  }
}
~/.codex/config.toml
[mcp_servers.data-kit]
url = "https://stagenth.com/mcp/data-kit/"
.cursor/mcp.json
{
  "mcpServers": {
    "data-kit": {
      "url": "https://stagenth.com/mcp/data-kit/"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "data-kit": {
      "url": "https://stagenth.com/mcp/data-kit/"
    }
  }
}

Available tools 6

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

data
data_clean
一步清洗脏数据：去重 / 去空白 / 删全空行列，产物落文件中转站并返清洗统计（1 credit/次）。
data_convert
把数据文件转成另一种格式（csv/json/ndjson/parquet/xlsx），产物存文件中转站返下载 URL（1 credit/次）。 典型：把大 CSV 转 parquet 便于后续分析、或把 JSON 日志转 xlsx 给人看。失败自动退款。
data_inspect
查看数据文件结构：列名/类型/行数/每列非空数 + 前 N 行预览。免费(0 credit)。 支持 CSV/TSV/JSON/NDJSON/Parquet。取数(data_query)前先调它看清有哪些列、哪些是数值。
data_join
两份数据文件按共同列连接（如 订单表×客户表），返回实际数据行 JSON（1 credit/次）。 跨文件对齐是单文件 data_query 做不到的；DuckDB 引擎、锁死文件/网络访问。失败自动退款。
data_profile
数据画像：每列类型/去重近似数/空值率 + 数值列 min/max/avg/std/分位数（1 credit/次）。 相当于 pandas df.describe()——AI 拿它一眼看清整份数据的分布与质量。失败自动退款。 返回 {ok, format, n_rows, n_cols, profile[]}。
data_query
查询 / 过滤 / 分组聚合数据文件，返回**实际数据行（JSON）**供 AI 直接分析（1 credit/次）。 支持 CSV/TSV/JSON/NDJSON/Parquet，两种用法： · 原始 SQL（表名固定 t）：sql="SELECT 商品, sum(销量) s FROM t GROUP BY 商品 ORDER BY s DESC LIMIT 5" · 结构化（不用写 SQL）：group_by=["地区"], measures=["销售额"], agg="sum", sort_by="销售额", descending=true, limit=10 SQL 仅允许单条只读 SELECT/WITH，禁止读文件/建表/联网。结果硬上限 1000 行，超出置 truncated=True。失败自动退款。 返回 {ok, format, mode, columns, total_rows, returned_rows, truncated, rows[]}。

Endpoints

URLTransportStateLatencyChecked
https://stagenth.com/mcp/data-kit/ streamable-http answering 5469 ms 6 min ago

stagenth · 数据工具箱 — questions

Answers built from our own checks of this server.

What can stagenth · 数据工具箱 do?
It exposes 6 tools, read directly from the server on our last check. Among them: data_clean, data_convert, data_inspect, data_join, data_profile, data_query. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
Is stagenth · 数据工具箱 working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 1211 ms. The bar chart above shows every period we have measured.
How do I connect stagenth · 数据工具箱?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does stagenth · 数据工具箱 need an API key?
No. stagenth · 数据工具箱 completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 6 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is stagenth · 数据工具箱?
It answers our handshake in 1211 ms on average, which is faster than 3% of all working MCP servers we measure. That is on the slow side — worth knowing if the tool sits inside an interactive loop. The comparison comes from our own checks across the whole registry, every 15 minutes.