by google
MCP Toolbox for Databases by Google. An open-source server that lets AI agents query Cloud SQL, Spanner, AlloyDB, and ot
Connects AI agents to Google Cloud databases (Cloud SQL, Spanner, AlloyDB) with built-in authentication and connection pooling. Handles the complexity of secure database access for AI applications.
Google GenAI Toolbox is an official MCP server published by google that provides AI assistants with tools and capabilities via the Model Context Protocol. MCP Toolbox for Databases by Google. An open-source server that lets AI agents query Cloud SQL, Spanner, AlloyDB, and ot It is categorized under databases, cloud infrastructure, ai ml.
You can install Google GenAI Toolbox in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
Apache-2.0
Google GenAI Toolbox is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Enable Claude to query your database directly using natural language
Example
Ask 'Show me top 10 customers by revenue this month' and get SQL results instantly
Eliminate manual SQL writing for ad-hoc queries, get insights 10x faster
Generate complex reports and analytics without leaving conversation
Example
Analyze sales trends, cohort retention, user behavior patterns conversationally
Democratize data access—non-technical team members can query databases
Understand database structure, relationships, and data models
Example
'Explain the user_orders table schema and its relationships'
Onboard engineers faster, explore unfamiliar databases efficiently
Share your MCP server with the developer community
We evaluated Google GenAI Toolbox against two servers with overlapping tools; this profile had the clearer scope statement.
Google GenAI Toolbox has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Google GenAI Toolbox is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Google GenAI Toolbox has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
We wired Google GenAI Toolbox into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Google GenAI Toolbox reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
I recommend Google GenAI Toolbox for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
According to our notes, Google GenAI Toolbox benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Useful MCP listing: Google GenAI Toolbox is the kind of server we cite when onboarding engineers to host + tool permissions.
Google GenAI Toolbox has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
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[!NOTE] MCP Toolbox for Databases is currently in beta, and may see breaking changes until the first stable release (v1.0).
MCP Toolbox for Databases is an open source MCP server for databases. It enables you to develop tools easier, faster, and more securely by handling the complexities such as connection pooling, authentication, and more.
This README provides a brief overview. For comprehensive details, see the full documentation.
<!-- TOC ignore:true -->[!NOTE] This solution was originally named “Gen AI Toolbox for Databases” as its initial development predated MCP, but was renamed to align with recently added MCP compatibility.
Toolbox helps you build Gen AI tools that let your agents access data in your database. Toolbox provides:
⚡ Supercharge Your Workflow with an AI Database Assistant ⚡
Stop context-switching and let your AI assistant become a true co-developer. By connecting your IDE to your databases with MCP Toolbox, you can delegate complex and time-consuming database tasks, allowing you to build faster and focus on what matters. This isn't just about code completion; it's about giving your AI the context it needs to handle the entire development lifecycle.
Here’s how it will save you time:
Learn how to connect your AI tools (IDEs) to Toolbox using MCP.
Toolbox sits between your application's orchestration framework and your database, providing a control plane that is used to modify, distribute, or invoke tools. It simplifies the management of your tools by providing you with a centralized location to store and update tools, allowing you to share tools between agents and applications and update those tools without necessarily redeploying your application.
<p align="center"> <img src="./docs/en/getting-started/introduction/architecture.png" alt="architecture" width="50%"/> </p>You can run Toolbox directly with a configuration file:
npx @toolbox-sdk/server --tools-file tools.yaml
This runs the latest version of the toolbox server with your configuration file.
[!NOTE] This method should only be used for non-production use cases such as experimentation. For any production use-cases, please consider Installing the server and then running it.
For the latest version, check the releases page and use the following instructions for your OS and CPU architecture.
<details open> <summary>Binary</summary>To install Toolbox as a binary:
<!-- {x-release-please-start-version} --><details> <summary>Linux (AMD64)</summary></details> <details> <summary>Container image</summary> You can also install Toolbox as a container:To install Toolbox as a binary on Linux (AMD64):
</details> <details> <summary>macOS (Apple Silicon)</summary># see releases page for other versions export VERSION=0.28.0 curl -L -o toolbox https://storage.googleapis.com/genai-toolbox/v$VERSION/linux/amd64/toolbox chmod +x toolboxTo install Toolbox as a binary on macOS (Apple Silicon):
</details> <details> <summary>macOS (Intel)</summary># see releases page for other versions export VERSION=0.28.0 curl -L -o toolbox https://storage.googleapis.com/genai-toolbox/v$VERSION/darwin/arm64/toolbox chmod +x toolboxTo install Toolbox as a binary on macOS (Intel):
</details> <details> <summary>Windows (Command Prompt)</summary># see releases page for other versions export VERSION=0.28.0 curl -L -o toolbox https://storage.googleapis.com/genai-toolbox/v$VERSION/darwin/amd64/toolbox chmod +x toolboxTo install Toolbox as a binary on Windows (Command Prompt):
</details> <details> <summary>Windows (PowerShell)</summary>:: see releases page for other versions set VERSION=0.28.0 curl -o toolbox.exe "https://storage.googleapis.com/genai-toolbox/v%VERSION%/windows/amd64/toolbox.exe"To install Toolbox as a binary on Windows (PowerShell):
</details># see releases page for other versions $VERSION = "0.28.0" curl.exe -o toolbox.exe "https://storage.googleapis.com/genai-toolbox/v$VERSION/windows/amd64/toolbox.exe"
# see releases page for other versions
export VERSION=0.28.0
docker pull us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:$VERSION
</details>
<details>
<summary>Homebrew</summary>
To install Toolbox using Homebrew on macOS or Linux:
brew install mcp-toolbox
</details>
<details>
<summary>Compile from source</summary>
To install from source, ensure you have the latest version of Go installed, and then run the following command:
go install github.com/googleapis/[email protected]
<!-- {x-release-please-end} -->
</details>
<details>
<summary>Gemini CLI Extensions</summary>
To install Gemini CLI Extensions for MCP Toolbox, run the following command:
gemini extensions install https://github.com/gemini-cli-extensions/mcp-toolbox
</details>
Configure a tools.yaml to define your tools, and then
execute toolbox to start the server:
To run Toolbox from binary:
./toolbox --tools-file "tools.yaml"
</details> <details> <summary>Container image</summary>ⓘ Note
Toolbox enables dynamic reloading by default. To disable, use the--disable-reloadflag.
To run the server after pulling the container image:
export VERSION=0.24.0 # Use the version you pulled
docker run -p 5000:5000 \
-v $(pwd)/tools.yaml:/app/tools.yaml \
us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:$VERSION \
--tools-file "/app/tools.yaml"
</details> <details> <summary>Source</summary>ⓘ Note
The-vflag mounts your localtools.yamlinto the container, and-pmaps the container's port5000to your host's port5000.
To run the server directly from source, navigate to the project root directory and run:
go run .
</details> <details> <summary>Homebrew</summary>ⓘ Note
This command runs the project from source, and is more suitable for development and testing. It does not compile a binary into your$GOPATH. If you want to compile a binary instead, refer the Developer Documentation.
If you installed Toolbox using Homebrew, the toolbox
binary is available in your system path. You can start the server with the same
command:
toolbox --tools-file "tools.yaml"
</details>
<details>
<
Run data quality queries to catch anomalies and inconsistencies
Example
Find duplicate records, missing values, orphaned foreign keys automatically
Maintain data integrity with less manual SQL work
Prerequisites
Time Estimate
15-30 minutes including configuration and testing
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
MCP server acts as bridge between Claude and database, translating natural language to SQL queries and returning results in structured format.
Protocols
Compatibility
✓ Use when
Use for ad-hoc data queries, exploratory analysis, report generation, schema exploration, and democratizing data access. Best for read-heavy analytics workloads.
✗ Avoid when
Avoid for production write operations, mission-critical transactions, real-time OLTP workloads, or when database contains sensitive PII without proper access controls. Use read replicas, not primary.