Connect BigQuery MCP to your AI Agents

Query petabytes of BigQuery data in plain English.

Example prompts

Everything you can ask your agent about your BigQuery data.

Ask in plain English — Sequel translates it into a BigQuery query, runs it, and your agent hands back the answer. No SQL, no dashboards, no CSV exports.

Connect to your agent
What you can ask your agent
  • What are the top 10 events by count this week?
  • Show me daily revenue for the past 30 days as a line chart
  • Which users had the highest session count last month?
  • What's the p95 query latency by dataset over the past 7 days?
  • List all tables in my analytics dataset with row counts

Install

Install BigQuery MCP in your agent

Pick your app and Sequel installs itself: a one-click link where the client supports it, that client’s own few steps where it doesn’t. Every route signs in with your Sequel account over OAuth, so there is no API key to copy and nothing to keep in sync.

Claude, ChatGPT, Cursor, VS Code, Claude Code, Codex, Grok, Muse, dots and any other MCP app

Already have an MCP client?

https://api.sequel.sh/mcp

Add it as a remote (streamable HTTP) server and sign in when prompted. Skills come with it; nothing else to install. Manual setup per client

Choose your app

  • Claude

    One click, opens in the app

  • Cursor

    One click, opens in the app

  • VS Code

    One click, opens in the app

  • ChatGPT

    Turn on developer mode, then add Sequel. About two minutes.

  • Claude Code

    Run one command, then sign in with /mcp.

  • Codex

    Run one command, then sign in.

  • Gemini CLI

    Run one command, then sign in with /mcp auth.

  • Grok

    Add Sequel as a connector and sign in.

  • Grok Bot

    Paste this to the bot. It registers Sequel and asks you to sign in.

  • Muse

    Muse writes its own connector. One message is the whole setup.

  • dots

    Add Sequel in ChatGPT; your dot picks it up with no extra step.

  • OpenCode

    Add Sequel as a remote server from the OpenCode CLI.

  • Other MCP app

    Any client that speaks remote MCP can connect with this URL.

Skills

Playbooks that run on BigQuery

Step-by-step procedures your agent follows on your BigQuery data, instead of improvising a query. Browse all skills

Can we trust our product metrics

Two tools show different numbers for the same metric and nobody knows which to trust. Reconciles the disputed figure against a system of record such as Stripe or the application database, then finds the instrumentation defect behind it: duplicate and near-duplicate event names, events that silently stopped firing, missing properties and system-fired events counted as user actions.

Feature launch impact readout

Measure whether a feature we just shipped actually landed: adoption against an eligible denominator of users who could even reach it, breadth, depth and sustained use after the release, a pre and post impact estimate with or without a control group, and a keep, iterate or sunset call.

Find our activation moment

Discover the aha moment: which early in-product action, taken in the first session or first week, most separates users who stay from users who vanish, how to score candidate first actions by retention lift, and what share of new signups ever reach it. Covers activation metric definition, activation rate and time to value.

Is our retention curve flattening

Do users keep coming back, or do they drift away after the first week or month? Builds the cohort retention curve for your key action at its natural frequency and judges whether it flattens to a plateau or decays to zero, covering N-day versus unbounded retention, repeat usage, leaky bucket diagnosis and how the plateau compares to published benchmarks.

Read out an A/B test honestly

Is this A/B test result real, or statistically significant only by accident? Runs the validity gates before reporting anything (sample ratio mismatch, peeking, power and minimum detectable effect, novelty), then gives absolute and relative lift with a confidence interval, a ship or kill call, and the winning variant extended through to revenue instead of stopping at the proxy metric.

Frequently asked questions

Do I need a service account key to connect BigQuery?

No. Sequel uses Google OAuth 2.0, so you authorize with your Google account directly — no JSON key files required. Sequel requests read-only access (bigquery.readonly scope) so it can only run SELECT queries.

What is a GCP Project ID and where do I find it?

The GCP Project ID is the unique identifier for your Google Cloud project (e.g. my-company-analytics-123). You can find it in the Google Cloud Console at the top of the dashboard, or by running `gcloud config get-value project` in your terminal.

Does Sequel support BigQuery legacy SQL?

No. Sequel generates standard SQL (GoogleSQL) only. Legacy SQL is deprecated by Google and is not supported.

Will Sequel see all my BigQuery datasets and tables?

Sequel will list all datasets your Google account has access to within the connected project. You can restrict schema introspection to specific datasets from the connection settings after connecting.

Are there query cost implications?

Yes — BigQuery charges for bytes scanned per query. Sequel generates efficient queries, but on very large tables you may want to apply partition filters. You can add instructions in the connection settings to guide the AI to always filter by partition columns.

Start analyzing your BigQuery data today

Connect in minutes — then ask across all your data, not just one source.