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Google Gemini

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Gemini is Google's AI assistant. This destination lets Gemini read data from any source you connect in Dataddo, so you can ask questions about your data in plain language. Dataddo delivers the data directly to the model and takes care of the rest.

Dataddo handles the whole pipeline for you. It keeps the data fresh, stores it in SmartCache, and serves it through a built-in querying layer. Every answer comes with metadata: technical metadata such as data freshness, and business metadata such as what each table and column means. You do not write any code.

How It Works

On the Data Anywhere and Enterprise plans, Gemini is a destination, and the data comes from the flows you attach to it. On the Data to AI plan, Gemini is an AI Model, and the data comes from the Contexts you attach to it. A Context is data that Dataddo keeps ready to query. When Gemini needs data, Dataddo serves it from SmartCache and returns the rows together with their freshness and business metadata.

Access is authorized with OAuth. You sign in to Dataddo from Gemini once, with your Dataddo email and password. Gemini then keeps the connection active and renews it in the background, so you do not handle any tokens.

What Gemini Can Do with Your Data

Dataddo exposes your data through its data MCP server at https://headless.dataddo.com/mcp-data. The server is a semantic layer: Gemini asks in business terms (customers, invoices, deals), and Dataddo never accepts SQL from the model. The tools fall into these groups:

Tools Purpose
list_flows, describe_flow See which flows are available to your account and what each one holds.
list_models, list_entities, describe_entity, search, sample_values Find the business entities, fields, relationships and metrics that can be queried.
query Query an entity by field names, with filters, grouping, date grains and predefined metrics.
data_status, known_gaps Check how fresh the data is and which questions the data cannot answer.
refresh, report_problem Request fresh data for an entity, or report an answer that looks wrong.

A flow or Context can be available but not yet queryable. The model can see it as soon as it is attached, but it can query it only after a semantic model covers it. list_flows reports this for each one.

Setup Overview

The steps depend on your Dataddo plan:

  • On the Data Anywhere and Enterprise plans, you work with sources, flows and destinations.
  • On the Data to AI plan, you work with Contexts and AI Models instead.
  1. Create a Google Gemini authorizer.
  2. Make your data available:
    • Data Anywhere and Enterprise: create a Google Gemini destination that uses the authorizer, then attach one or more flows to it.
    • Data to AI: create a Google Gemini AI Model that uses the authorizer, then attach one or more Contexts to it.
  3. Add the Dataddo server in Gemini CLI and sign in with your Dataddo account.

After you sign in, Gemini can access every flow or Context attached to an AI destination or AI Model in your Dataddo account, not only the ones attached to Google Gemini. Their data appears after they run for the first time.

Authorize Connection to Google Gemini

Authorize the connection so Dataddo can serve your data to Gemini:

  1. Go to Authorizers and click Authorize New Service.
  2. Select Google Gemini.
  3. Fill in the field below and click Save. Dataddo validates the connection when you save it.
Field Description
Label A name for this authorizer in Dataddo.

Make Your Data Available to Google Gemini

Follow the steps for your plan.

Data Anywhere and Enterprise Plans

  1. Go to Destinations, click Create Destination, and select Google Gemini.
  2. Enter a name, choose the authorizer you created, and click Save.
  3. Go to Flows and click Create Flow.
  4. Add one or more sources.
  5. Add the Google Gemini destination.
  6. Set the schedule that keeps the data fresh and click Save.

Data to AI Plan

  1. Go to AI Models and add a new one.
  2. Select Google Gemini.
  3. Enter a name and choose the authorizer you created.
  4. Attach one or more Contexts to the AI Model.
  5. Click Save.

Set Up the Connection in Gemini CLI

  1. Open the settings file: ~/.gemini/settings.json for all projects, or .gemini/settings.json in a project root for one project.
  2. Add the Dataddo server to the mcpServers section. Only the URL is needed. Do not add headers or an oauth block, because Gemini CLI discovers the Dataddo sign-in automatically.
{
  "mcpServers": {
    "dataddo": {
      "httpUrl": "https://headless.dataddo.com/mcp-data"
    }
  }
}
  1. Use httpUrl, not url (which is the legacy SSE transport).
  2. Restart Gemini CLI and run /mcp auth dataddo. A browser window opens with the Dataddo sign-in page.
  3. Enter your Dataddo email and password, and complete multi-factor authentication if you are asked to.
  4. Run /mcp to confirm the dataddo server connects and lists its tools.

Gemini CLI stores the credentials in ~/.gemini/mcp-oauth-tokens.json and renews them automatically. The sign-in needs a web browser on the same machine, so it does not work in a remote SSH session or another environment without a browser.

The same configuration enables Dataddo tools in Gemini Code Assist agent mode.

Troubleshooting

  • A flow or Context is missing: attach it to an AI destination or AI Model in the Dataddo account you signed in with, then let it run.
  • Gemini CLI asks you to sign in again: the sign-in expired or was revoked. Run /mcp auth dataddo and sign in to Dataddo.
  • The sign-in page does not open: check that the server uses httpUrl set to exactly https://headless.dataddo.com/mcp-data and that you run Gemini CLI on a machine with a web browser.
  • A flow or Context is listed but Gemini cannot query it: it is available but no semantic model covers it yet.
  • Gemini cannot fetch data: check that the flow has run at least once, so the Context holds data.
  • Stale data: review the flow schedule. Dataddo serves the most recent data it has stored for the Context.

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