How to integrate Google BigQuery MCP with Kimi Code

How to integrate Google BigQuery MCP with Kimi Code Kimi Code is Moonshot AI's open-source coding agent, powered by Kimi K2.6. It runs in your terminal, reads and edits code, executes shell commands, and plans multi-step tasks, with native MCP support for extending it to outside tools. In this guide, I will explain the easiest and most secure way to connect your Google BigQuery account to Kimi Code via Composio Connect, so it can run yesterday's sales summary query, find top 10 customers by revenue, analyze traffic data for last quarter, and more without ever putting your account credentials at risk.

Get started for freeGet a demo
Google BigQuery logoGoogle BigQuery
Oauth2Google Service Account

Google BigQuery is a fully managed cloud data warehouse for fast SQL analytics on massive datasets. It's designed to help you analyze big data with ease, speed, and built-in machine learning.

63 Tools

How to integrate Google BigQuery MCP with Kimi Code

Kimi Code is Moonshot AI's open-source coding agent, powered by Kimi K2.6. It runs in your terminal, reads and edits code, executes shell commands, and plans multi-step tasks, with native MCP support for extending it to outside tools.

In this guide, I will explain the easiest and most secure way to connect your Google BigQuery account to Kimi Code via Composio Connect, so it can run yesterday's sales summary query, find top 10 customers by revenue, analyze traffic data for last quarter, and more without ever putting your account credentials at risk.

Also integrate Google BigQuery with

ChatGPTAntigravityOpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenCodeCursorVS CodeOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

Why use Composio?

Composio provides:

  • Access to 1,000+ managed apps from a single MCP endpoint. This makes it convenient for agents to run cross-app workflows.
  • Managed OAuth. You do not have to worry about authentication and authorization flows for every app.
  • Programmatic tool calling. Allows LLMs to write code in a remote workbench to handle complex tool chaining. This reduces back-and-forth for frequent tool calls.
  • Large tool response handling outside the LLM context. This minimizes context bloat from large tool responses.
  • Dynamic just-in-time access to thousands of tools across hundreds of apps. Composio loads the tools your agent needs, so LLMs are not overwhelmed by tools they do not need.

Connect Google BigQuery to Kimi Code

Kimi Code is a TypeScript agent distributed through npm. It acts as an MCP client and reads server definitions from an mcp.json file, and it can also add and authenticate servers conversationally through /mcp-config. Composio is a remote HTTP server that authenticates with OAuth, so no API key is stored anywhere.

1. Install Kimi Code

The quickest way is the official install script, which requires no pre-installed Node.js and places the kimi executable on your PATH.

bash
# macOS or Linux
curl -fsSL https://code.kimi.com/kimi-code/install.sh | bash

# Windows PowerShell
irm https://code.kimi.com/kimi-code/install.ps1 | iex

# Confirm the installation
kimi --version

2. Log in

Start Kimi Code in your project directory, then sign in from the interactive UI:

bash
kimi

Run /login and choose Kimi Code OAuth using the device-code flow, or use a Moonshot API key.

3. Add Composio with /mcp-config

In current versions of Kimi Code, MCP servers are managed inside the app, not with a shell subcommand. From the interactive UI, run:

bash
/mcp-config
Kimi Code MCP config flow for adding the Composio MCP server

Tell it the server name and URL in plain language. For example:

Server name is Composio, and here is the server URL: https://connect.composio.dev/mcp

Kimi Code asks whether to add it globally, at ~/.kimi-code/mcp.json, or project-local for the current checkout, then writes the entry for you:

bash
{
  "mcpServers": {
    "Composio": {
      "url": "https://connect.composio.dev/mcp"
    }
  }
}

There is no transport field to set. Kimi Code infers HTTP from the url.

4. Restart the session

The new server is picked up on a fresh session, not the current one. Start a new session:

bash
/new

On the new session, Kimi Code detects that the server needs authorization and prompts you to run:

bash
/mcp-config login Composio

5. Authorize with OAuth

Run the command Kimi suggests:

bash
/mcp-config login composio

Kimi Code opens Composio's authorization page or surfaces a URL. Approve access, then return to the session. You should see confirmation that the Composio MCP server is connected.

Composio authorization page for Kimi Code MCP setup

Check the connection status any time with /mcp. Composio should appear as connected with its tools listed.

Kimi Code showing Composio connected after OAuth authorization

Connect your Google BigQuery account

Back in a Kimi Code session, ask the agent to connect to Google BigQuery or give it any Google BigQuery-related task.

For example, ask it to:

  • "Run yesterday's sales summary query"
  • "Find top 10 customers by revenue"
  • "Analyze traffic data for last quarter"

It will prompt you to authenticate and authorize access to Google BigQuery.

That is it. Composio tools are now available in Kimi Code, and your Google BigQuery account is ready to use.

Conclusion

You have successfully connected Google BigQuery to Kimi Code using Composio Connect. Your agent can now manage Google BigQuery from the terminal with natural language, without exposing credentials in prompts or local scripts.

Since the same Composio endpoint exposes 1,000+ apps, you can add Slack, Calendar, Linear, and more to the same server and chain them into cross-app workflows.

TOOLS

Supported Tools

Every Google BigQuery action and event your agent gets out of the box.

Cancel BigQuery Job

Tool to cancel a running BigQuery job.

Create Capacity Commitment

Tool to create a new capacity commitment resource in BigQuery Reservation.

Create BigQuery Connection

Tool to create a new BigQuery connection to external data sources using the BigQuery Connection API.

Create Analytics Hub Data Exchange

Tool to create a new Analytics Hub data exchange for sharing BigQuery datasets.

Create Analytics Hub Listing

Tool to create a new listing in a BigQuery Analytics Hub data exchange.

Create BigQuery Dataset

Tool to create a new BigQuery dataset with explicit location, labels, and description using the BigQuery Datasets API.

Create Analytics Hub Listing

Tool to create a new listing in a data exchange using Analytics Hub API.

Create BigQuery Data Policy (v2beta1)

Tool to create a new data policy under a project with specified location using the v2beta1 BigQuery Data Policy API.

Create Analytics Hub Query Template

Tool to create a new query template in a BigQuery Analytics Hub Data Clean Room (DCR) data exchange.

Create BigQuery Reservation

Tool to create a new BigQuery reservation resource to guarantee compute capacity (slots) for query and pipeline jobs.

Create BigQuery Reservation Assignment

Tool to create a BigQuery reservation assignment that allows a project, folder, or organization to submit jobs using slots from a specified reservation.

Create BigQuery Routine

Tool to create a new user-defined routine (function or procedure) in a BigQuery dataset.

Create BigQuery Table

Tool to create a new, empty table in a BigQuery dataset.

Delete BigQuery Dataset

Tool to delete a BigQuery dataset specified by datasetId via the datasets.

Delete BigQuery Job Metadata

Tool to delete the metadata of a BigQuery job.

Delete BigQuery ML Model

Tool to delete a BigQuery ML model from a dataset.

Delete BigQuery Routine

Tool to delete a BigQuery routine by its ID.

Delete BigQuery Table

Tool to delete a BigQuery table from a dataset.

Get BigQuery ML Model

Tool to retrieve a specific BigQuery ML model resource by model ID.

Get BigQuery Connection IAM Policy

Tool to get the IAM access control policy for a BigQuery connection resource.

Get BigQuery Dataset Metadata

Tool to retrieve BigQuery dataset metadata including location via the datasets.

Get BigQuery Job

Tool to retrieve information about a specific BigQuery job.

Get BigQuery Query Results

Tool to get the results of a BigQuery query job via RPC.

Get BigQuery Routine

Tool to retrieve a BigQuery routine (user-defined function or stored procedure) by its ID.

Get BigQuery Routine IAM Policy

Tool to retrieve the IAM access control policy for a BigQuery routine resource.

Get BigQuery Service Account

Tool to get the service account for a project used for interactions with Google Cloud KMS.

Get BigQuery Table IAM Policy

Tool to retrieve the IAM access control policy for a BigQuery table resource.

Get BigQuery Table Schema

Tool to fetch a BigQuery table's schema and metadata without querying row data.

Insert Data into BigQuery Table

Tool to stream data into BigQuery one record at a time without running a load job.

Insert BigQuery Job

Tool to start a new asynchronous BigQuery job (query, load, extract, or copy).

Insert BigQuery Job with Upload

Tool to start a new BigQuery load job with file upload.

List Analytics Hub Listings

Tool to list all listings in a given Analytics Hub data exchange.

List BigQuery Connections

Tool to list BigQuery connections in a given project and location.

List BigQuery Capacity Commitments

Tool to list all capacity commitments for the admin project.

List Data Exchange Listings

Tool to list all listings in a given Analytics Hub data exchange using the v1beta1 API.

List BigQuery Datasets

Tool to list datasets in a specific BigQuery project, including dataset locations.

List BigQuery Jobs

Tool to list all jobs that you started in a BigQuery project.

List BigQuery Data Transfer Locations

Tool to list information about supported locations for BigQuery Data Transfer Service.

List Connections in Location

Tool to list BigQuery connections in a given project and location using the v1beta1 API.

List BigQuery Location Data Policies

Tool to list all data policies in a specified parent project and location using the v2beta1 API.

List BigQuery Models

Tool to list all BigQuery ML models in a specified dataset.

List Organization Data Exchanges

Tool to list all data exchanges from projects in a given organization and location using Analytics Hub API.

List BigQuery Projects

Tool to list BigQuery projects to which the user has been granted any project role.

List Analytics Hub Query Templates

Tool to list all query templates in a given Analytics Hub data exchange.

List BigQuery Reservation Assignments

Tool to list BigQuery reservation assignments.

List BigQuery Reservation Groups

Tool to list all BigQuery reservation groups for a project in a specified location.

List BigQuery Reservations

Tool to list all BigQuery reservations for a project in a specified location.

List BigQuery Routines

Tool to list all routines (user-defined functions and stored procedures) in a BigQuery dataset.

List BigQuery Row Access Policies

Tool to list all row access policies on a specified BigQuery table.

List BigQuery Table Data

Tool to list the content of a BigQuery table in rows via the REST API.

List BigQuery Tables

Tool to list tables in a BigQuery dataset via the REST API.

Patch BigQuery Dataset

Tool to update an existing BigQuery dataset using RFC5789 PATCH semantics.

Patch BigQuery ML Model

Tool to update specific fields in an existing BigQuery ML model using PATCH semantics.

Patch BigQuery Table

Tool to update specific fields in an existing BigQuery table using RFC5789 PATCH semantics.

Query

Query Tool runs a SQL query in BigQuery using the REST API.

Search All BigQuery Reservation Assignments

Tool to search all BigQuery reservation assignments for a specified resource in a particular region.

Set BigQuery Routine IAM Policy

Tool to set the IAM access control policy for a BigQuery routine resource.

Test BigQuery Routine IAM Permissions

Tool to test which IAM permissions the caller has on a BigQuery routine.

Undelete BigQuery Dataset

Tool to undelete a BigQuery dataset within the time travel window.

Update BigQuery Connection

Tool to update a specified BigQuery connection using the BigQuery Connection API.

Update BigQuery Dataset

Tool to update information in an existing BigQuery dataset using the PUT method.

Update BigQuery Routine

Tool to update an existing BigQuery routine (function or stored procedure).

Update BigQuery Table

Tool to update an existing BigQuery table.

FRAMEWORKS

How to build Google BigQuery MCP Agent with another framework

ChatGPT logo

ChatGPT

Use Google BigQuery MCP with ChatGPT

Antigravity logo

Antigravity

Use Google BigQuery MCP with Antigravity

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Google BigQuery MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Google BigQuery MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Google BigQuery MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Google BigQuery MCP with Claude Cowork

Codex logo

Codex

Use Google BigQuery MCP with Codex

Cursor logo

Cursor

Use Google BigQuery MCP with Cursor

VS Code logo

VS Code

Use Google BigQuery MCP with VS Code

OpenCode logo

OpenCode

Use Google BigQuery MCP with OpenCode

OpenClaw logo

OpenClaw

Use Google BigQuery MCP with OpenClaw

Hermes logo

Hermes

Use Google BigQuery MCP with Hermes

CLI logo

CLI

Use Google BigQuery MCP with CLI

Google ADK logo

Google ADK

Use Google BigQuery MCP with Google ADK

LangChain logo

LangChain

Use Google BigQuery MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Google BigQuery MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Google BigQuery MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Google BigQuery MCP with LlamaIndex

CrewAI logo

CrewAI

Use Google BigQuery MCP with CrewAI

FAQ

Frequently asked questions

With a standalone Google BigQuery MCP server, the agents and LLMs can only access a fixed set of Google BigQuery tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Google BigQuery and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Kimi Code fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Google BigQuery tools.

Yes, absolutely. You can configure which Google BigQuery scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Google BigQuery data and credentials are handled as safely as possible.

Start with Google BigQuery.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Google BigQuery tool your agent needs.Free to start.

Start building
Customer stories

Teams ship real agents on Composio

GET STARTED FOR FREEBOOK A DEMO
agent.aiZoomLettaGleanHubSpotAWSWabi

Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati
Harsha Gaddipati
Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya
Abhi Arya
Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave
Nirman Dave
CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu
Ryan Yu
Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola
Tomisin Jenrola
Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche
Jerome Leclanche
Co-Founder, Ingram Technologies