Docs & Usage Guide

MCP Toolbox for Databases

[!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.

[!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.

Why Toolbox?

Toolbox helps you build Gen AI tools that let your agents access data in your database. Toolbox provides:

Simplified development: Integrate tools to your agent in less than 10 lines of code, reuse tools between multiple agents or frameworks, and deploy new versions of tools more easily.
Better performance: Best practices such as connection pooling, authentication, and more.
Enhanced security: Integrated auth for more secure access to your data
End-to-end observability: Out of the box metrics and tracing with built-in support for OpenTelemetry.

⚡ 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:

Query in Plain English: Interact with your data using natural language right from your IDE. Ask complex questions like, "How many orders were delivered in 2024, and what items were in them?" without writing any SQL.
Automate Database Management: Simply describe your data needs, and let the AI assistant manage your database for you. It can handle generating queries, creating tables, adding indexes, and more.
Generate Context-Aware Code: Empower your AI assistant to generate application code and tests with a deep understanding of your real-time database schema. This accelerates the development cycle by ensuring the generated code is directly usable.
Slash Development Overhead: Radically reduce the time spent on manual setup and boilerplate. MCP Toolbox helps streamline lengthy database configurations, repetitive code, and error-prone schema migrations.

Learn how to connect your AI tools (IDEs) to Toolbox using MCP.

General Architecture

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.

architecture

Getting Started

Installing the server

For the latest version, check the releases page and use the following instructions for your OS and CPU architecture.

Binary

To install Toolbox as a binary:

# see releases page for other versions
export VERSION=0.10.0
curl -O https://storage.googleapis.com/genai-toolbox/v$VERSION/linux/amd64/toolbox
chmod +x toolbox

Container image

You can also install Toolbox as a container:

# see releases page for other versions
export VERSION=0.10.0
docker pull us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:$VERSION

Homebrew

To install Toolbox using Homebrew on macOS or Linux:

brew install mcp-toolbox

Compile from source

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]

Running the server

Configure a tools.yaml to define your tools, and then execute toolbox to start the server:

./toolbox --tools-file "tools.yaml"

[!NOTE] Toolbox enables dynamic reloading by default. To disable, use the --disable-reload flag.

Homebrew Users

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"

You can use toolbox help for a full list of flags! To stop the server, send a terminate signal (ctrl+c on most platforms).

For more detailed documentation on deploying to different environments, check out the resources in the How-to section

Integrating your application

Once your server is up and running, you can load the tools into your application. See below the list of Client SDKs for using various frameworks:

Python (Github)

Core
Install Toolbox Core SDK:
pip install toolbox-core
Load tools:
from toolbox_core import ToolboxClient

# update the url to point to your server
async with ToolboxClient("http://127.0.0.1:5000") as client:

    # these tools can be passed to your application!
    tools = await client.load_toolset("toolset_name")
For more detailed instructions on using the Toolbox Core SDK, see the project's README.
LangChain / LangGraph
Install Toolbox LangChain SDK:
pip install toolbox-langchain
Load tools:
from toolbox_langchain import ToolboxClient

# update the url to point to your server
async with ToolboxClient("http://127.0.0.1:5000") as client:

    # these tools can be passed to your application!
    tools = client.load_toolset()
For more detailed instructions on using the Toolbox LangChain SDK, see the project's README.
LlamaIndex
Install Toolbox Llamaindex SDK:
pip install toolbox-llamaindex
Load tools:
from toolbox_llamaindex import ToolboxClient

# update the url to point to your server
async with ToolboxClient("http://127.0.0.1:5000") as client:

    # these tools can be passed to your application!
    tools = client.load_toolset()
For more detailed instructions on using the Toolbox Llamaindex SDK, see the project's README.

Javascript/Typescript (Github)

Core

Install Toolbox Core SDK:
```
npm install @toolbox-sdk/core
```

Load tools:

import { ToolboxClient } from '@toolbox-sdk/core';

// update the url to point to your server
const URL = 'http://127.0.0.1:5000';
let client = new ToolboxClient(URL);

// these tools can be passed to your application!
const tools = await client.loadToolset('toolsetName');

For more detailed instructions on using the Toolbox Core SDK, see the project's README.

LangChain / LangGraph

Install Toolbox Core SDK:
```
npm install @toolbox-sdk/core
```

Load tools:

import { ToolboxClient } from '@toolbox-sdk/core';

// update the url to point to your server
const URL = 'http://127.0.0.1:5000';
let client = new ToolboxClient(URL);

// these tools can be passed to your application!
const toolboxTools = await client.loadToolset('toolsetName');

// Define the basics of the tool: name, description, schema and core logic
const getTool = (toolboxTool) => tool(currTool, {
    name: toolboxTool.getName(),
    description: toolboxTool.getDescription(),
    schema: toolboxTool.getParamSchema()
});

// Use these tools in your Langchain/Langraph applications
const tools = toolboxTools.map(getTool);

Genkit

Install Toolbox Core SDK:
```
npm install @toolbox-sdk/core
```

Load tools:

import { ToolboxClient } from '@toolbox-sdk/core';
import { genkit } from 'genkit';

// Initialise genkit
const ai = genkit({
    plugins: [
        googleAI({
            apiKey: process.env.GEMINI_API_KEY || process.env.GOOGLE_API_KEY
        })
    ],
    model: googleAI.model('gemini-2.0-flash'),
});

// update the url to point to your server
const URL = 'http://127.0.0.1:5000';
let client = new ToolboxClient(URL);

// these tools can be passed to your application!
const toolboxTools = await client.loadToolset('toolsetName');

// Define the basics of the tool: name, description, schema and core logic
const getTool = (toolboxTool) => ai.defineTool({
    name: toolboxTool.getName(),
    description: toolboxTool.getDescription(),
    schema: toolboxTool.getParamSchema()
}, toolboxTool)

// Use these tools in your Genkit applications
const tools = toolboxTools.map(getTool);

Go (Github)

Core

Install Toolbox Go SDK:

go get github.com/googleapis/mcp-toolbox-sdk-go

Load tools:

package main

import (
  "github.com/googleapis/mcp-toolbox-sdk-go/core"
  "context"
)

func main() {
  // Make sure to add the error checks
  // update the url to point to your server
  URL := "http://127.0.0.1:5000";
  ctx := context.Background()

  client, err := core.NewToolboxClient(URL)

  // Framework agnostic tools
  tools, err := client.LoadToolset("toolsetName", ctx)
}

For more detailed instructions on using the Toolbox Go SDK, see the project's README.

LangChain Go

Install Toolbox Go SDK:

go get github.com/googleapis/mcp-toolbox-sdk-go

Load tools:

package main

import (
  "context"
  "encoding/json"

  "github.com/googleapis/mcp-toolbox-sdk-go/core"
  "github.com/tmc/langchaingo/llms"
)

func main() {
  // Make sure to add the error checks
  // update the url to point to your server
  URL := "http://127.0.0.1:5000"
  ctx := context.Background()

  client, err := core.NewToolboxClient(URL)

  // Framework agnostic tool
  tool, err := client.LoadTool("toolName", ctx)

  // Fetch the tool's input schema
  inputschema, err := tool.InputSchema()

  var paramsSchema map[string]any
  _ = json.Unmarshal(inputschema, &paramsSchema)

  // Use this tool with LangChainGo
  langChainTool := llms.Tool{
    Type: "function",
    Function: &llms.FunctionDefinition{
      Name:        tool.Name(),
      Description: tool.Description(),
      Parameters:  paramsSchema,
    },
  }
}

Genkit

Install Toolbox Go SDK:

go get github.com/googleapis/mcp-toolbox-sdk-go

Load tools:

package main
import (
  "context"
  "encoding/json"

  "github.com/firebase/genkit/go/ai"
  "github.com/firebase/genkit/go/genkit"
  "github.com/googleapis/mcp-toolbox-sdk-go/core"
  "github.com/googleapis/mcp-toolbox-sdk-go/tbgenkit"
  "github.com/invopop/jsonschema"
)

func main() {
  // Make sure to add the error checks
  // Update the url to point to your server
  URL := "http://127.0.0.1:5000"
  ctx := context.Background()
  g, err := genkit.Init(ctx)

  client, err := core.NewToolboxClient(URL)

  // Framework agnostic tool
  tool, err := client.LoadTool("toolName", ctx)

  // Convert the tool using the tbgenkit package
  // Use this tool with Genkit Go
  genkitTool, err := tbgenkit.ToGenkitTool(tool, g)
  if err != nil {
    log.Fatalf("Failed to convert tool: %v\n", err)
  }
}

Go GenAI

Install Toolbox Go SDK:

go get github.com/googleapis/mcp-toolbox-sdk-go

Load tools:

package main

import (
  "context"
  "encoding/json"

  "github.com/googleapis/mcp-toolbox-sdk-go/core"
  "google.golang.org/genai"
)

func main() {
  // Make sure to add the error checks
  // Update the url to point to your server
  URL := "http://127.0.0.1:5000"
  ctx := context.Background()

  client, err := core.NewToolboxClient(URL)

  // Framework agnostic tool
  tool, err := client.LoadTool("toolName", ctx)

  // Fetch the tool's input schema
  inputschema, err := tool.InputSchema()

  var schema *genai.Schema
  _ = json.Unmarshal(inputschema, &schema)

  funcDeclaration := &genai.FunctionDeclaration{
    Name:        tool.Name(),
    Description: tool.Description(),
    Parameters:  schema,
  }

  // Use this tool with Go GenAI
  genAITool := &genai.Tool{
    FunctionDeclarations: []*genai.FunctionDeclaration{funcDeclaration},
  }
}

OpenAI Go

Install Toolbox Go SDK:

go get github.com/googleapis/mcp-toolbox-sdk-go

Load tools:

package main

import (
  "context"
  "encoding/json"

  "github.com/googleapis/mcp-toolbox-sdk-go/core"
  openai "github.com/openai/openai-go"
)

func main() {
  // Make sure to add the error checks
  // Update the url to point to your server
  URL := "http://127.0.0.1:5000"
  ctx := context.Background()

  client, err := core.NewToolboxClient(URL)

  // Framework agnostic tool
  tool, err := client.LoadTool("toolName", ctx)

  // Fetch the tool's input schema
  inputschema, err := tool.InputSchema()

  var paramsSchema openai.FunctionParameters
  _ = json.Unmarshal(inputschema, &paramsSchema)

  // Use this tool with OpenAI Go
  openAITool := openai.ChatCompletionToolParam{
    Function: openai.FunctionDefinitionParam{
      Name:        tool.Name(),
      Description: openai.String(tool.Description()),
      Parameters:  paramsSchema,
    },
  }

}

Configuration

The primary way to configure Toolbox is through the tools.yaml file. If you have multiple files, you can tell toolbox which to load with the --tools-file tools.yaml flag.

You can find more detailed reference documentation to all resource types in the Resources.

Sources

The sources section of your tools.yaml defines what data sources your Toolbox should have access to. Most tools will have at least one source to execute against.

sources:
  my-pg-source:
    kind: postgres
    host: 127.0.0.1
    port: 5432
    database: toolbox_db
    user: toolbox_user
    password: my-password

For more details on configuring different types of sources, see the Sources.

Tools

The tools section of a tools.yaml define the actions an agent can take: what kind of tool it is, which source(s) it affects, what parameters it uses, etc.

tools:
  search-hotels-by-name:
    kind: postgres-sql
    source: my-pg-source
    description: Search for hotels based on name.
    parameters:
      - name: name
        type: string
        description: The name of the hotel.
    statement: SELECT * FROM hotels WHERE name ILIKE '%' || $1 || '%';

For more details on configuring different types of tools, see the Tools.

Toolsets

The toolsets section of your tools.yaml allows you to define groups of tools that you want to be able to load together. This can be useful for defining different groups based on agent or application.

toolsets:
    my_first_toolset:
        - my_first_tool
        - my_second_tool
    my_second_toolset:
        - my_second_tool
        - my_third_tool

You can load toolsets by name:

# This will load all tools
all_tools = client.load_toolset()

# This will only load the tools listed in 'my_second_toolset'
my_second_toolset = client.load_toolset("my_second_toolset")

Versioning

This project uses semantic versioning, including a MAJOR.MINOR.PATCH version number that increments with:

MAJOR version when we make incompatible API changes
MINOR version when we add functionality in a backward compatible manner
PATCH version when we make backward compatible bug fixes

The public API that this applies to is the CLI associated with Toolbox, the interactions with official SDKs, and the definitions in the tools.yaml file.

Contributing

Contributions are welcome. Please, see the CONTRIBUTING to get started.

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms. See Contributor Code of Conduct for more information.

Community

Join our discord community to connect with our developers!

MCP Toolbox For Databases

Docs & Usage Guide

MCP Toolbox for Databases

Table of Contents

Why Toolbox?

General Architecture

Getting Started

Installing the server

Running the server

Homebrew Users

Integrating your application

Configuration

Sources

Tools

Toolsets

Versioning

Contributing

Community

MCP Toolbox For Databases

Docs & Usage Guide

MCP Toolbox for Databases

Table of Contents

Why Toolbox?

General Architecture

Getting Started

Installing the server

Running the server

Homebrew Users

Integrating your application

Configuration

Sources

Tools

Toolsets

Versioning

Contributing

Community

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