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mcp-toolbox MCP工具 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
mcp-toolbox MCP工具 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/googleapis/mcp-toolbox
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"mcp-toolbox-mcp--": {
"command": "npx",
"args": ["-y", "mcp-toolbox"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 mcp-toolbox MCP工具 执行以下任务... Claude: [自动调用 mcp-toolbox MCP工具 MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"mcp-toolbox_mcp__": {
"command": "npx",
"args": ["-y", "mcp-toolbox"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效

You can run Toolbox directly with a configuration file:
npx @toolbox-sdk/server --config tools.yaml
This runs the latest version of the Toolbox server with your configuration file.
[!NOTE] This method is optimized for convenience rather than performance. For a more standard and reliable installation, please use the binary or container image as described in Install & Run the Toolbox server.
For the latest version, check the [releases page][releases] and use the following instructions for your OS and CPU architecture.
[releases]: https://github.com/googleapis/mcp-toolbox/releases
<details open> <summary>Binary</summary>
To install Toolbox as a binary:
<details> <summary>Linux (AMD64)</summary> To install Toolbox as a binary on Linux (AMD64):</details> <details> <summary>macOS (Apple Silicon)</summary> To install Toolbox as a binary on macOS (Apple Silicon):> # see releases page for other versions > export VERSION=1.5.0 > curl -L -o toolbox https://storage.googleapis.com/mcp-toolbox-for-databases/v$VERSION/linux/amd64/toolbox > chmod +x toolbox ></details> <details> <summary>macOS (Intel)</summary> To install Toolbox as a binary on macOS (Intel):> # see releases page for other versions > export VERSION=1.5.0 > curl -L -o toolbox https://storage.googleapis.com/mcp-toolbox-for-databases/v$VERSION/darwin/arm64/toolbox > chmod +x toolbox ></details> <details> <summary>Windows (Command Prompt)</summary> To install Toolbox as a binary on Windows (Command Prompt):> # see releases page for other versions > export VERSION=1.5.0 > curl -L -o toolbox https://storage.googleapis.com/mcp-toolbox-for-databases/v$VERSION/darwin/amd64/toolbox > chmod +x toolbox ></details> <details> <summary>Windows (PowerShell)</summary> To install Toolbox as a binary on Windows (PowerShell):> :: see releases page for other versions > set VERSION=1.5.0 > curl -o toolbox.exe "https://storage.googleapis.com/mcp-toolbox-for-databases/v%VERSION%/windows/amd64/toolbox.exe" ></details> <details> <summary>Windows ARM64 (Command Prompt)</summary> To install Toolbox as a binary on Windows ARM64 (Command Prompt):> # see releases page for other versions > $VERSION = "1.5.0" > curl.exe -o toolbox.exe "https://storage.googleapis.com/mcp-toolbox-for-databases/v$VERSION/windows/amd64/toolbox.exe" ></details> <details> <summary>Windows ARM64 (PowerShell)</summary> To install Toolbox as a binary on Windows ARM64 (PowerShell):> :: see releases page for other versions > set VERSION=1.5.0 > curl -o toolbox.exe "https://storage.googleapis.com/mcp-toolbox-for-databases/v%VERSION%/windows/arm64/toolbox.exe" ></details> </details>> # see releases page for other versions > $VERSION = "1.5.0" > curl.exe -o toolbox.exe "https://storage.googleapis.com/mcp-toolbox-for-databases/v$VERSION/windows/arm64/toolbox.exe" >
<details> <summary>Container image</summary> You can also install Toolbox as a container:
```sh
npm install -g @google/gemini-cli
gemini extensions install https://github.com/gemini-cli-extensions/cloud-sql-postgres
gemini extensions install https://github.com/gemini-cli-extensions/mcp-toolbox ``` </details>
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 query your data in plain English, automate schema discovery and management, and generate database-aware code.
You can use the Toolbox in any MCP-compatible IDE or client (e.g., Gemini CLI, Google Antigravity, Claude Code, Codex, etc.) by configuring the MCP server.
Prebuilt tools are also conveniently available via the Google Antigravity MCP Store with a simple click-to-install experience.
mcp.json or claude_desktop_config.json): {
"mcpServers": {
"toolbox-postgres": {
"command": "npx",
"args": [
"-y",
"@toolbox-sdk/server",
"--prebuilt=postgres",
"--stdio"
]
}
}
}
When you run Toolbox with a --prebuilt=<database> flag, you instantly get access to standard tools to interact with that database. You can also specify a specific toolset using the --prebuilt=<database>/<toolset> syntax (e.g., --prebuilt=postgres/data to only load SQL tools).
Supported databases currently include: - Google Cloud: AlloyDB, BigQuery, Cloud SQL (PostgreSQL, MySQL, SQL Server), Spanner, Firestore, Knowledge Catalog (formerly known as Dataplex). - Other Databases: PostgreSQL, MySQL, MariaDB, SQL Server, Oracle, MongoDB, Redis, Elasticsearch, CockroachDB, ClickHouse, Couchbase, Neo4j, Snowflake, Trino, and more.
For a full list of available tools and their capabilities across all supported databases, see the Prebuilt Tools Reference.
See the Install & Run the Toolbox server section for different execution methods like Docker or binaries.
[!TIP] For users looking for a managed solution, Google Cloud MCP Servers provide a managed MCP experience with prebuilt tools; you can learn more about the differences here.
---
Toolbox can also be used as a framework for customized tools. 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 `--config tools.yaml` flag.
You can find more detailed reference documentation to all resource types in the Resources.
Toolbox Client SDKs provide the easy-to-use building blocks and advanced features for connecting your custom applications to the MCP Toolbox server. See below the list of Client SDKs for using various frameworks:
<details open> <summary>Python (<a href="https://github.com/googleapis/mcp-toolbox-sdk-python">Github</a>)</summary> <br> <blockquote>
<details open> <summary>Core</summary>
pip install toolbox-core
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][toolbox-core-readme].
[toolbox-core]: https://pypi.org/project/toolbox-core/ [toolbox-core-readme]: https://github.com/googleapis/mcp-toolbox-sdk-python/tree/main/packages/toolbox-core/README.md
</details> <details> <summary>LangChain / LangGraph</summary>
pip install toolbox-langchain
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][toolbox-langchain-readme].
[toolbox-langchain]: https://pypi.org/project/toolbox-langchain/ [toolbox-langchain-readme]: https://github.com/googleapis/mcp-toolbox-sdk-python/blob/main/packages/toolbox-langchain/README.md
</details> <details> <summary>LlamaIndex</summary>
pip install toolbox-llamaindex
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][toolbox-llamaindex-readme].
[toolbox-llamaindex]: https://pypi.org/project/toolbox-llamaindex/ [toolbox-llamaindex-readme]: https://github.com/googleapis/genai-toolbox-llamaindex-python/blob/main/README.md
</details> </details> </blockquote> <details> <summary>Javascript/Typescript (<a href="https://github.com/googleapis/mcp-toolbox-sdk-js">Github</a>)</summary> <br> <blockquote>
<details open> <summary>Core</summary>
npm install @toolbox-sdk/core
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][toolbox-core-js-readme].
[toolbox-core-js]: https://www.npmjs.com/package/@toolbox-sdk/core [toolbox-core-js-readme]: https://github.com/googleapis/mcp-toolbox-sdk-js/blob/main/packages/toolbox-core/README.md
</details> <details> <summary>LangChain / LangGraph</summary>
npm install @toolbox-sdk/core
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);
</details> <details> <summary>Genkit</summary>
npm install @toolbox-sdk/core
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);
</details> <details> <summary>ADK</summary>
npm install @toolbox-sdk/adk
import { ToolboxClient } from '@toolbox-sdk/adk';
// 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 ADK SDK, see the [project's README][toolbox-adk-js-readme].
[toolbox-adk-js]: https://www.npmjs.com/package/@toolbox-sdk/adk [toolbox-adk-js-readme]: https://github.com/googleapis/mcp-toolbox-sdk-js/blob/main/packages/toolbox-adk/README.md
</details> </details> </blockquote> <details> <summary>Go (<a href="https://github.com/googleapis/mcp-toolbox-sdk-go">Github</a>)</summary> <br> <blockquote>
<details> <summary>Core</summary>
go get github.com/googleapis/mcp-toolbox-sdk-go
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][toolbox-core-go-readme].
[toolbox-go]: https://pkg.go.dev/github.com/googleapis/mcp-toolbox-sdk-go/core [toolbox-core-go-readme]: https://github.com/googleapis/mcp-toolbox-sdk-go/blob/main/core/README.md
</details> <details> <summary>LangChain Go</summary>
go get github.com/googleapis/mcp-toolbox-sdk-go
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, ¶msSchema)
// Use this tool with LangChainGo
langChainTool := llms.Tool{
Type: "function",
Function: &llms.FunctionDefinition{
Name: tool.Name(),
Description: tool.Description(),
Parameters: paramsSchema,
},
}
}
</details> <details> <summary>Genkit</summary>
go get github.com/googleapis/mcp-toolbox-sdk-go
package main
import (
"context"
"log"
"github.com/firebase/genkit/go/genkit"
"github.com/googleapis/mcp-toolbox-sdk-go/core"
"github.com/googleapis/mcp-toolbox-sdk-go/tbgenkit"
)
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 := 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)
}
log.Printf("Successfully converted tool: %s", genkitTool.Name())
}
</details> <details> <summary>Go GenAI</summary>
go get github.com/googleapis/mcp-toolbox-sdk-go
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},
}
}
</details> <details> <summary>OpenAI Go</summary>
go get github.com/googleapis/mcp-toolbox-sdk-go
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, ¶msSchema)
// Use this tool with OpenAI Go
openAITool := openai.ChatCompletionToolParam{
Function: openai.FunctionDefinitionParam{
Name: tool.Name(),
Description: openai.String(tool.Description()),
Parameters: paramsSchema,
},
}
}
</details> <details open> <summary>ADK Go</summary>
go get github.com/googleapis/mcp-toolbox-sdk-go
package main
import (
"github.com/googleapis/mcp-toolbox-sdk-go/tbadk"
"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 := tbadk.NewToolboxClient(URL)
if err != nil {
return fmt.Sprintln("Could not start Toolbox Client", err)
}
// Use this tool with ADK Go
tool, err := client.LoadTool("toolName", ctx)
if err != nil {
return fmt.Sprintln("Could not load Toolbox Tool", err)
}
}
For more detailed instructions on using the Toolbox Go SDK, see the [project's README][toolbox-core-go-readme].
</details> </details> </blockquote> </details>
---
/extensions list
成熟的MCP数据库中间件,Stars超15k说明生产应用广泛。Go语言高效,支持多数据库是核心优势,适合构建智能数据交互系统。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ Apache 2.0 — 宽松开源协议,可商用,需保留版权声明和 NOTICE 文件,含专利授权条款。
AI Skill Hub 点评:mcp-toolbox MCP工具 的核心功能完整,质量优秀。对于Claude Desktop / Claude Code 用户来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。
| 原始名称 | mcp-toolbox |
| 原始描述 | 开源MCP工具:MCP Toolbox for Databases is an open source MCP server for databases.。⭐15.2k · Go |
| Topics | MCP服务器数据库集成AI AgentGo开发多数据库支持 |
| GitHub | https://github.com/googleapis/mcp-toolbox |
| License | Apache-2.0 |
| 语言 | Go |
收录时间:2026-05-14 · 更新时间:2026-05-16 · License:Apache-2.0 · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端