datatomcp

com.datatomcp由 datatomcp.com 發布官方發布者v1.3.0更新於 Nov 5, 2026

AI-native data layer: sheets, databases and apps for every agent, with exact answers and audit.

已驗證Streamable HTTP可網頁執行資料庫檔案與儲存資料與分析

概覽

AI 產生的概覽

託管式資料層,讓 AI 助理查詢團隊的試算表、檔案與資料庫,回傳精確、帶版本的结果並保留稽核紀錄。

可以做什麼
  • 瀏覽資料集:列出資料集與列數、更新時間,檢視欄位、型別、定義與關聯,取得工作區總覽
  • 查詢資料:篩選、排序、分頁讀取資料列,依欄位分組計數、加總、平均,列出欄位的實際值
  • 視覺化:在對話中把查詢結果畫成圖表
  • 儀表板:建立、列出並重新整理工作區中的儀表板
  • 向團隊送出資料問題說明
適用情境
適合資料散落在 Google Sheets、CSV 或 Excel 檔、PostgreSQL、MySQL、Stripe、HubSpot、Airtable,且沒有專職資料團隊的情境。當需要精確彙總、共用指標定義,並記錄代理問過什麼時特別合適。
執行需求
遠端 streamable HTTP 端點,無需安裝。需要帳號並以 OAuth 登入(支援動態用戶端註冊),授權可隨時撤銷。須先連接資料來源:上傳檔案、在 Google 選擇器中指定試算表,或連接 PostgreSQL、MySQL、Stripe、HubSpot、Airtable。僅支援本機伺服器的用戶端需透過 mcp-remote 之類的橋接。免費版有額度限制,Pro 為付費方案。
安裝前請注意
代理可讀取已連接的資料,因此資料集中的內容會暴露給助理;每個連線可限制在部分工作區。寫入類工具會建立儀表板或向團隊送出說明,因而改動共用工作區內容。資料託管於歐盟,聲明不用於訓練。內建 AI 功能預設關閉,需手動開啟。更高額度需付費 Pro 方案。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 datatomcp,將其新增到工作區。
  2. 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
  3. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/com.datatomcp%2Fdatatomcp/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。 客戶端會在首次連接時完成 OAuth 登入。

{
  "mcpServers": {
    "datatomcp": {
      "type": "http",
      "url": "https://app.datatomcp.com/mcp"
    }
  }
}

README

[datatomcp]

The AI-native data layer for teams without a data team. Your team's data, ready for every AI agent.

Website · Start free · Guides · Demo video

[Listed on mcpservers.org]


datatomcp is one governed place for a team's data, that every AI agent can ask: Google Sheets, CSV and Excel files, PostgreSQL and MySQL, Stripe, HubSpot and Airtable. Connect your data once: datatomcp links the datasets, drafts definitions of what each number means for a person to approve, and records every question an agent asks. Agents (Claude, ChatGPT, Cursor, n8n and others) query it over MCP or REST, and a database computes the answer, so totals are exact. News: datatomcp is now an AI-native data layer (4 Nov 2026).

  • Hosted. Nothing to install or run. One URL works in every client that supports remote MCP servers.
  • OAuth sign-in. No API key to paste into your agent. You can revoke access at any time.
  • Exact, versioned results. Counts, sums and averages come from DuckDB. Every result names the dataset version it came from and links to the rows behind it.
  • Shared definitions. Approved definitions like paid_revenue and a glossary of your team's words. Agents use them by name, and the answer says who approved the definition.
  • Audit trail. Every agent question is kept: who asked, from which agent, the query, the data version. Repeated questions are compared. Export as CSV.
  • Linked datasets. Orders, customers and regions in one question, with unmatched rows counted.
  • Charts and dashboards. The chart tool draws the answer in the chat (52 chart types, as an MCP Apps view). Agents make dashboards from your questions and refresh them later; dashboards never change your data.
  • Workspaces. Owners, editors and viewers; each agent connection can be limited to some workspaces.
  • Private Google Sheets. You pick the sheet in Google's file picker, and datatomcp can read that file only. Pro syncs within 5 minutes of an edit.
  • Import report. Bad lines, numbers stored as text and mixed date formats are reported before any agent sees the data.
  • Read-only data. Agents can query your data, but they can't change it or run raw SQL. The only tools that write create dashboards or send your team a note.
  • Hosted in the EU. Your data is never used for training. AI features inside datatomcp (cleaning suggestions, an assistant on your own key) are off until you turn them on.

This repository holds the public documentation and client configuration. The service itself runs at app.datatomcp.com.

Server

URLhttps://app.datatomcp.com/mcp
TransportStreamable HTTP
AuthOAuth 2.1 (dynamic client registration and client ID metadata documents)
Registry namecom.datatomcp/datatomcp

Quick start

  1. Sign up at app.datatomcp.com (free, no card).
  2. Add a dataset: upload a CSV or Excel file, choose a Google Sheet, or connect PostgreSQL, MySQL, Stripe, HubSpot or Airtable. New accounts start with an example dataset.
  3. Add the server to your client (below), sign in when asked, and ask a question about your data.

Tools

ToolWhat it does
workspace_overviewEvery dataset with what its columns mean, the approved definitions, the links between datasets and example questions, in one call
list_datasetsYour datasets, with row counts and freshness
describe_datasetColumns, types, example values, approved definitions, glossary, links to other datasets, data warnings and today's date
query_rowsFilter, sort, select columns and paginate (up to 1,000 rows per call)
aggregateGroup by columns; count, distinct count, sum, average, min and max, or a saved definition by name
distinct_valuesThe real values in a column, so filters match exactly
chartDraws a query's answer as a chart in the conversation, with the takeaway as the title
create_dashboardMakes a dashboard (a one-page board or a short story of slides) in your workspace
list_dashboardsThe workspace's dashboards
refresh_dashboardRe-runs a dashboard on the current data
report_issueSends your team a note about a data problem

Filters support eq, neq, gt, gte, lt, lte, in, not_in, contains, starts_with, between, is_null and not_null.

Client setup

Claude (Claude.ai and Claude Desktop)

Settings → Connectors → Add custom connector. Paste https://app.datatomcp.com/mcp, name it datatomcp, connect, and allow access.

Claude Code

bash
claude mcp add --transport http datatomcp https://app.datatomcp.com/mcp

Then run /mcp, choose datatomcp and sign in.

ChatGPT

Settings → Apps & Connectors → Advanced, and turn on developer mode. Create a connector with the URL above and OAuth authentication, then sign in.

Cursor

Settings → MCP → Add new server. Choose type HTTP and use the URL above. Cursor asks you to log in the first time.

VS Code

.vscode/mcp.json:

json
{  "servers": {    "datatomcp": { "type": "http", "url": "https://app.datatomcp.com/mcp" }  }}

Windsurf

~/.codeium/windsurf/mcp_config.json:

json
{  "mcpServers": {    "datatomcp": { "serverUrl": "https://app.datatomcp.com/mcp" }  }}

Cline

Open the MCP Servers panel → Remote Servers, name it datatomcp, and use the URL above. Or add it to cline_mcp_settings.json:

json
{  "mcpServers": {    "datatomcp": { "type": "streamableHttp", "url": "https://app.datatomcp.com/mcp" }  }}

Antigravity

Customizations → MCP servers → View raw config (mcp_config.json):

json
{  "mcpServers": {    "datatomcp": { "serverUrl": "https://app.datatomcp.com/mcp" }  }}

Click Refresh, then Authenticate.

OpenCode

opencode.json:

json
{  "$schema": "https://opencode.ai/config.json",  "mcp": {    "datatomcp": { "type": "remote", "url": "https://app.datatomcp.com/mcp" }  }}

Codex

bash
codex mcp add datatomcp --url https://app.datatomcp.com/mcpcodex mcp login datatomcp

Gemini CLI

bash
gemini mcp add --transport http datatomcp https://app.datatomcp.com/mcp

Then run /mcp auth datatomcp.

Clients with local (stdio) servers only

Use mcp-remote as a bridge. It handles the sign-in:

json
{  "mcpServers": {    "datatomcp": { "command": "npx", "args": ["-y", "mcp-remote", "https://app.datatomcp.com/mcp"] }  }}

Example

How many orders came from France in September, and what was the revenue?

The agent calls describe_dataset to learn the columns, then one aggregate call:

json
{  "dataset_id": "ds_orders",  "where": [    { "column": "country", "op": "eq", "value": "France" },    { "column": "order_date", "op": "between", "value": ["2026-09-01", "2026-09-30"] }  ],  "metrics": [    { "fn": "count", "as": "orders" },    { "fn": "sum", "column": "total", "as": "revenue" }  ]}

On our 50,000-row test sheet, it answers with 277 orders and €50,279.50 in revenue. The tool result is 32 bytes, not the whole sheet.

REST API

The same datasets, definitions and query engine are available over REST with an API key, for apps and automations such as n8n, Make or Zapier. Reference: datatomcp.com/docs/api. OpenAPI 3.1: datatomcp.com/openapi.json.

Plans

FreePro ($12 or €12 a month)
Datasets325
Rows per dataset100,0002,000,000
Queries per day1,00050,000
Workspaces1, 2 people3, 5 people each
Audit history30 days90 days
Google Sheets syncOn demandWithin 5 minutes

Guides

Support

Questions, bugs or a file that doesn't import the way you expect: [email protected], or open an issue in this repository.

License

The documentation and configuration in this repository are MIT licensed. The datatomcp service is proprietary.

來源:README.md,提交 e0605be

工具

0
該伺服器需要登入,因此 SourceWeft 無法在沒有帳號的情況下讀取其工具,也未收錄。已連接帳號所能看到的內容可能因帳號及其權限而異。

版本歷史

2
  1. v1.3.0最新Nov 5, 2026
  2. v1.0.0Oct 21, 2026

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