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---
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title: "Core Package"
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linkTitle: "Core"
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type: docs
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weight: 1
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---
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# MCP Toolbox Core SDK
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[](https://opensource.org/licenses/Apache-2.0)
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This SDK allows you to seamlessly integrate the functionalities of
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[Toolbox](https://github.com/googleapis/genai-toolbox) allowing you to load and
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use tools defined in the service as standard Go structs within your GenAI
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applications.
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This simplifies integrating external functionalities (like APIs, databases, or
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custom logic) managed by the Toolbox into your workflows, especially those
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involving Large Language Models (LLMs).
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<!-- TOC ignore:true -->
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<!-- TOC -->
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- [MCP Toolbox Core SDK](#mcp-toolbox-core-sdk)
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- [Installation](#installation)
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- [Quickstart](#quickstart)
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- [Usage](#usage)
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- [Transport Protocols](#transport-protocols)
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- [Supported Protocols](#supported-protocols)
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- [Example](#example)
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- [Loading Tools](#loading-tools)
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- [Load a toolset](#load-a-toolset)
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- [Load a single tool](#load-a-single-tool)
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- [Invoking Tools](#invoking-tools)
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- [Client to Server Authentication](#client-to-server-authentication)
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- [When is Client-to-Server Authentication Needed?](#when-is-client-to-server-authentication-needed)
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- [How it works](#how-it-works)
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- [Configuration](#configuration)
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- [Authenticating with Google Cloud Servers](#authenticating-with-google-cloud-servers)
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- [Step by Step Guide for Cloud Run](#step-by-step-guide-for-cloud-run)
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- [Authenticating Tools](#authenticating-tools)
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- [When is Authentication Needed?](#when-is-authentication-needed)
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- [Supported Authentication Mechanisms](#supported-authentication-mechanisms)
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- [Step 1: Configure Tools in Toolbox Service](#step-1-configure-tools-in-toolbox-service)
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- [Step 2: Configure SDK Client](#step-2-configure-sdk-client)
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- [Provide an ID Token Retriever Function](#provide-an-id-token-retriever-function)
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- [Option A: Add Default Authentication to a Client](#option-a-add-default-authentication-to-a-client)
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- [Option B: Add Authentication to a Loaded Tool](#option-b-add-authentication-to-a-loaded-tool)
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- [Option C: Add Authentication While Loading Tools](#option-c-add-authentication-while-loading-tools)
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- [Complete Authentication Example](#complete-authentication-example)
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- [Binding Parameter Values](#binding-parameter-values)
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- [Why Bind Parameters?](#why-bind-parameters)
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- [Option A: Add Default Bound Parameters to a Client](#option-a-add-default-bound-parameters-to-a-client)
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- [Option B: Binding Parameters to a Loaded Tool](#option-b-binding-parameters-to-a-loaded-tool)
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- [Option C: Binding Parameters While Loading Tools](#option-c-binding-parameters-while-loading-tools)
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- [Binding Dynamic Values](#binding-dynamic-values)
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- [Using with Orchestration Frameworks](#using-with-orchestration-frameworks)
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- [Contributing](#contributing)
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- [License](#license)
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- [Support](#support)
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<!-- /TOC -->
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## Installation
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```bash
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go get github.com/googleapis/mcp-toolbox-sdk-go
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```
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This SDK is supported on Go version 1.24.4 and higher.
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> [!NOTE]
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>
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> - While the SDK itself is synchronous, you can execute its functions within goroutines to achieve asynchronous behavior.
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## Quickstart
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Here's a minimal example to get you started. Ensure your Toolbox service is
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running and accessible.
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```go
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package main
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import (
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"context"
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"fmt"
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"github.com/googleapis/mcp-toolbox-sdk-go/core"
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)
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func quickstart() string {
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ctx := context.Background()
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inputs := map[string]any{"location": "London"}
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client, err := core.NewToolboxClient("http://localhost:5000")
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if err != nil {
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return fmt.Sprintln("Could not start Toolbox Client", err)
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}
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tool, err := client.LoadTool("get_weather", ctx)
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if err != nil {
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return fmt.Sprintln("Could not load Toolbox Tool", err)
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}
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result, err := tool.Invoke(ctx, inputs)
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if err != nil {
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return fmt.Sprintln("Could not invoke tool", err)
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}
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return fmt.Sprintln(result)
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}
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func main() {
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fmt.Println(quickstart())
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}
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```
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## Usage
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Import and initialize a Toolbox client, pointing it to the URL of your running
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Toolbox service.
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```go
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import "github.com/googleapis/mcp-toolbox-sdk-go/core"
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client, err := core.NewToolboxClient("http://localhost:5000")
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```
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All interactions for loading and invoking tools happen through this client.
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> [!NOTE]
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> For advanced use cases, you can provide an external custom `http.Client`
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> during initialization (e.g., `core.NewToolboxClient(URL, core.WithHTTPClient(myClient)`). If you
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> provide your own session, you are responsible for managing its lifecycle;
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> `ToolboxClient` *will not* close it.
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> [!IMPORTANT]
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> Closing the `ToolboxClient` also closes the underlying network session shared by
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> all tools loaded from that client. As a result, any tool instances you have
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> loaded will cease to function and will raise an error if you attempt to invoke
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> them after the client is closed.
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## Transport Protocols
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The SDK supports multiple transport protocols for communicating with the Toolbox server. By default, the client uses the latest supported version of the **Model Context Protocol (MCP)**.
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You can explicitly select a protocol using the `core.WithProtocol` option during client initialization. This is useful if you need to use the native Toolbox HTTP protocol or pin the client to a specific legacy version of MCP.
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> [!NOTE]
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> * **Native Toolbox Transport**: This uses the service's native **REST over HTTP** API.
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> * **MCP Transports**: These options use the **Model Context Protocol over HTTP**.
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### Supported Protocols
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| Constant | Description |
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| :--- | :--- |
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| `core.MCP` | **(Default)** Alias for the latest supported MCP version (currently `v2025-06-18`). |
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| `core.Toolbox` | The native Toolbox HTTP protocol. |
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| `core.MCPv20250618` | MCP Protocol version 2025-06-18. |
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| `core.MCPv20250326` | MCP Protocol version 2025-03-26. |
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| `core.MCPv20241105` | MCP Protocol version 2024-11-05. |
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### Example
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If you wish to use the native Toolbox protocol:
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```go
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import "github.com/googleapis/mcp-toolbox-sdk-go/core"
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client, err := core.NewToolboxClient(
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"http://localhost:5000",
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core.WithProtocol(core.Toolbox),
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)
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```
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If you want to pin the MCP Version 2025-03-26:
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```go
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import "github.com/googleapis/mcp-toolbox-sdk-go/core"
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client, err := core.NewToolboxClient(
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"http://localhost:5000",
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core.WithProtocol(core.MCPv20250326),
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)
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```
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## Loading Tools
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You can load tools individually or in groups (toolsets) as defined in your
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Toolbox service configuration. Loading a toolset is convenient when working with
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multiple related functions, while loading a single tool offers more granular
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control.
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### Load a toolset
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A toolset is a collection of related tools. You can load all tools in a toolset
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or a specific one:
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```go
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// Load default toolset by providing an empty string as the name
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tools, err := client.LoadToolset("", ctx)
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// Load a specific toolset
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tools, err := client.LoadToolset("my-toolset", ctx)
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```
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### Load a single tool
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Loads a specific tool by its unique name. This provides fine-grained control.
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```go
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tool, err = client.LoadTool("my-tool", ctx)
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```
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## Invoking Tools
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Once loaded, tools behave like Go structs. You invoke them using `Invoke` method
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by passing arguments corresponding to the parameters defined in the tool's
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configuration within the Toolbox service.
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```go
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tool, err = client.LoadTool("my-tool", ctx)
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inputs := map[string]any{"location": "London"}
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result, err := tool.Invoke(ctx, inputs)
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```
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> [!TIP]
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> For a more comprehensive guide on setting up the Toolbox service itself, which
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> you'll need running to use this SDK, please refer to the [Toolbox Quickstart
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> Guide](https://googleapis.github.io/genai-toolbox/getting-started/local_quickstart).
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## Client to Server Authentication
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This section describes how to authenticate the ToolboxClient itself when
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connecting to a Toolbox server instance that requires authentication. This is
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crucial for securing your Toolbox server endpoint, especially when deployed on
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platforms like Cloud Run, GKE, or any environment where unauthenticated access is restricted.
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This client-to-server authentication ensures that the Toolbox server can verify
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the identity of the client making the request before any tool is loaded or
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called. It is different from [Authenticating Tools](#authenticating-tools),
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which deals with providing credentials for specific tools within an already
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connected Toolbox session.
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### When is Client-to-Server Authentication Needed?
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You'll need this type of authentication if your Toolbox server is configured to
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deny unauthenticated requests. For example:
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- Your Toolbox server is deployed on Cloud Run and configured to "Require authentication."
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- Your server is behind an Identity-Aware Proxy (IAP) or a similar
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authentication layer.
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- You have custom authentication middleware on your self-hosted Toolbox server.
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Without proper client authentication in these scenarios, attempts to connect or
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make calls (like `LoadTool`) will likely fail with `Unauthorized` errors.
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### How it works
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The `ToolboxClient` allows you to specify TokenSources that dynamically generate HTTP headers for
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every request sent to the Toolbox server. The most common use case is to add an
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Authorization header with a bearer token (e.g., a Google ID token).
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These header-generating functions are called just before each request, ensuring
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that fresh credentials or header values can be used.
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### Configuration
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You can configure these dynamic headers as seen below:
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```go
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import "github.com/googleapis/mcp-toolbox-sdk-go/core"
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tokenProvider := func() string {
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return "header3_value"
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}
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staticTokenSource := oauth2.StaticTokenSource(&oauth2.Token{AccessToken: "header2_value"})
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dynamicTokenSource := core.NewCustomTokenSource(tokenProvider)
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client, err := core.NewToolboxClient(
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"toolbox-url",
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core.WithClientHeaderString("header1", "header1_value"),
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core.WithClientHeaderTokenSource("header2", staticTokenSource),
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core.WithClientHeaderTokenSource("header3", dynamicTokenSource),
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)
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```
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### Authenticating with Google Cloud Servers
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For Toolbox servers hosted on Google Cloud (e.g., Cloud Run) and requiring
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`Google ID token` authentication, the helper module
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[auth_methods](https://github.com/googleapis/mcp-toolbox-sdk-go/blob/main/core/auth.go) provides utility functions.
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### Step by Step Guide for Cloud Run
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1. **Configure Permissions**: [Grant](https://cloud.google.com/run/docs/securing/managing-access#service-add-principals) the `roles/run.invoker` IAM role on the Cloud
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Run service to the principal. This could be your `user account email` or a
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`service account`.
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2. **Configure Credentials**
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- Local Development: Set up
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[ADC](https://cloud.google.com/docs/authentication/set-up-adc-local-dev-environment).
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- Google Cloud Environments: When running within Google Cloud (e.g., Compute
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Engine, GKE, another Cloud Run service, Cloud Functions), ADC is typically
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configured automatically, using the environment's default service account.
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3. **Connect to the Toolbox Server**
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```go
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import "github.com/googleapis/mcp-toolbox-sdk-go/core"
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import "context"
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ctx := context.Background()
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token, err := core.GetGoogleIDToken(ctx, URL)
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client, err := core.NewToolboxClient(
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URL,
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core.WithClientHeaderString("Authorization", token),
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)
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// Now, you can use the client as usual.
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```
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## Authenticating Tools
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|
> [!WARNING]
|
|
|
|
|
> **Always use HTTPS** to connect your application with the Toolbox service,
|
|
|
|
|
> especially in **production environments** or whenever the communication
|
|
|
|
|
> involves **sensitive data** (including scenarios where tools require
|
|
|
|
|
> authentication tokens). Using plain HTTP lacks encryption and exposes your
|
|
|
|
|
> application and data to significant security risks, such as eavesdropping and
|
|
|
|
|
> tampering.
|
|
|
|
|
|
|
|
|
|
Tools can be configured within the Toolbox service to require authentication,
|
|
|
|
|
ensuring only authorized users or applications can invoke them, especially when
|
|
|
|
|
accessing sensitive data.
|
|
|
|
|
|
|
|
|
|
### When is Authentication Needed?
|
|
|
|
|
|
|
|
|
|
Authentication is configured per-tool within the Toolbox service itself. If a
|
|
|
|
|
tool you intend to use is marked as requiring authentication in the service, you
|
|
|
|
|
must configure the SDK client to provide the necessary credentials (currently
|
|
|
|
|
Oauth2 tokens) when invoking that specific tool.
|
|
|
|
|
|
|
|
|
|
### Supported Authentication Mechanisms
|
|
|
|
|
|
|
|
|
|
The Toolbox service enables secure tool usage through **Authenticated Parameters**.
|
|
|
|
|
For detailed information on how these mechanisms work within the Toolbox service and how to configure them, please refer to [Toolbox Service Documentation - Authenticated Parameters](https://googleapis.github.io/genai-toolbox/resources/tools/#authenticated-parameters).
|
|
|
|
|
|
|
|
|
|
### Step 1: Configure Tools in Toolbox Service
|
|
|
|
|
|
|
|
|
|
First, ensure the target tool(s) are configured correctly in the Toolbox service
|
|
|
|
|
to require authentication. Refer to the [Toolbox Service Documentation -
|
|
|
|
|
Authenticated
|
|
|
|
|
Parameters](https://googleapis.github.io/genai-toolbox/resources/tools/#authenticated-parameters)
|
|
|
|
|
for instructions.
|
|
|
|
|
|
|
|
|
|
### Step 2: Configure SDK Client
|
|
|
|
|
|
|
|
|
|
Your application needs a way to obtain the required Oauth2 token for the
|
|
|
|
|
authenticated user. The SDK requires you to provide a function capable of
|
|
|
|
|
retrieving this token *when the tool is invoked*.
|
|
|
|
|
|
|
|
|
|
#### Provide an ID Token Retriever Function
|
|
|
|
|
|
|
|
|
|
You must provide the SDK with a function that returns the
|
|
|
|
|
necessary token when called. The implementation depends on your application's
|
|
|
|
|
authentication flow (e.g., retrieving a stored token, initiating an OAuth flow).
|
|
|
|
|
|
|
|
|
|
> [!IMPORTANT]
|
|
|
|
|
> The name used when registering the getter function with the SDK (e.g.,
|
|
|
|
|
> `"my_api_token"`) must exactly match the `name` of the corresponding
|
|
|
|
|
> `authServices` defined in the tool's configuration within the Toolbox service.
|
|
|
|
|
|
|
|
|
|
```go
|
|
|
|
|
func getAuthToken() string {
|
|
|
|
|
// ... Logic to retrieve ID token (e.g., from local storage, OAuth flow)
|
|
|
|
|
// This example just returns a placeholder. Replace with your actual token retrieval.
|
|
|
|
|
return "YOUR_ID_TOKEN" // Placeholder
|
|
|
|
|
}
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
> [!TIP]
|
|
|
|
|
> Your token retriever function is invoked every time an authenticated parameter
|
|
|
|
|
> requires a token for a tool call. Consider implementing caching logic within
|
|
|
|
|
> this function to avoid redundant token fetching or generation, especially for
|
|
|
|
|
> tokens with longer validity periods or if the retrieval process is
|
|
|
|
|
> resource-intensive.
|
|
|
|
|
|
|
|
|
|
#### Option A: Add Default Authentication to a Client
|
|
|
|
|
|
|
|
|
|
You can add default tool level authentication to a client.
|
|
|
|
|
Every tool / toolset loaded by the client will contain the auth token.
|
|
|
|
|
|
|
|
|
|
```go
|
|
|
|
|
|
|
|
|
|
ctx := context.Background()
|
|
|
|
|
|
|
|
|
|
client, err := core.NewToolboxClient("http://127.0.0.1:5000",
|
|
|
|
|
core.WithDefaultToolOptions(
|
|
|
|
|
core.WithAuthTokenString("my-auth-1", "auth-value"),
|
|
|
|
|
),
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
AuthTool, err := client.LoadTool("my-tool", ctx)
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
#### Option B: Add Authentication to a Loaded Tool
|
|
|
|
|
|
|
|
|
|
You can add the token retriever function to a tool object *after* it has been
|
|
|
|
|
loaded. This modifies the specific tool instance.
|
|
|
|
|
|
|
|
|
|
```go
|
|
|
|
|
|
|
|
|
|
ctx := context.Background()
|
|
|
|
|
|
|
|
|
|
client, err := core.NewToolboxClient("http://127.0.0.1:5000")
|
|
|
|
|
|
|
|
|
|
tool, err := client.LoadTool("my-tool", ctx)
|
|
|
|
|
|
|
|
|
|
AuthTool, err := tool.ToolFrom(
|
|
|
|
|
core.WithAuthTokenSource("my-auth", headerTokenSource),
|
|
|
|
|
core.WithAuthTokenString("my-auth-1", "value"),
|
|
|
|
|
)
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
#### Option C: Add Authentication While Loading Tools
|
|
|
|
|
|
|
|
|
|
You can provide the token retriever(s) directly during the `LoadTool` or
|
|
|
|
|
`LoadToolset` calls. This applies the authentication configuration only to the
|
|
|
|
|
tools loaded in that specific call, without modifying the original tool objects
|
|
|
|
|
if they were loaded previously.
|
|
|
|
|
|
|
|
|
|
```go
|
|
|
|
|
AuthTool, err := client.LoadTool("my-tool", ctx, core.WithAuthTokenString("my-auth-1", "value"))
|
|
|
|
|
|
|
|
|
|
// or
|
|
|
|
|
|
|
|
|
|
AuthTools, err := client.LoadToolset(
|
|
|
|
|
"my-toolset",
|
|
|
|
|
ctx,
|
|
|
|
|
core.WithAuthTokenString("my-auth-1", "value"),
|
|
|
|
|
)
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
> [!NOTE]
|
|
|
|
|
> Adding auth tokens during loading only affect the tools loaded within that
|
|
|
|
|
> call.
|
|
|
|
|
|
|
|
|
|
### Complete Authentication Example
|
|
|
|
|
|
|
|
|
|
```go
|
|
|
|
|
import "github.com/googleapis/mcp-toolbox-sdk-go/core"
|
|
|
|
|
import "fmt"
|
|
|
|
|
|
|
|
|
|
func getAuthToken() string {
|
|
|
|
|
// ... Logic to retrieve ID token (e.g., from local storage, OAuth flow)
|
|
|
|
|
// This example just returns a placeholder. Replace with your actual token retrieval.
|
|
|
|
|
return "YOUR_ID_TOKEN" // Placeholder
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
func main() {
|
|
|
|
|
ctx := context.Background()
|
|
|
|
|
inputs := map[string]any{"input": "some input"}
|
|
|
|
|
|
|
|
|
|
dynamicTokenSource := core.NewCustomTokenSource(getAuthToken)
|
|
|
|
|
|
|
|
|
|
client, err := core.NewToolboxClient("http://127.0.0.1:5000")
|
|
|
|
|
tool, err := client.LoadTool("my-tool", ctx)
|
|
|
|
|
AuthTool, err := tool.ToolFrom(core.WithAuthTokenSource("my_auth", dynamicTokenSource))
|
|
|
|
|
|
|
|
|
|
result, err := AuthTool.Invoke(ctx, inputs)
|
|
|
|
|
|
|
|
|
|
fmt.Println(result)
|
|
|
|
|
}
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
> [!NOTE]
|
|
|
|
|
> An auth token getter for a specific name (e.g., "GOOGLE_ID") will replace any
|
|
|
|
|
> client header with the same name followed by "_token" (e.g.,
|
|
|
|
|
> "GOOGLE_ID_token").
|
|
|
|
|
|
|
|
|
|
## Binding Parameter Values
|
|
|
|
|
|
|
|
|
|
The SDK allows you to pre-set, or "bind", values for specific tool parameters
|
|
|
|
|
before the tool is invoked or even passed to an LLM. These bound values are
|
|
|
|
|
fixed and will not be requested or modified by the LLM during tool use.
|
|
|
|
|
|
|
|
|
|
### Why Bind Parameters?
|
|
|
|
|
|
|
|
|
|
- **Protecting sensitive information:** API keys, secrets, etc.
|
|
|
|
|
- **Enforcing consistency:** Ensuring specific values for certain parameters.
|
|
|
|
|
- **Pre-filling known data:** Providing defaults or context.
|
|
|
|
|
|
|
|
|
|
> [!IMPORTANT]
|
|
|
|
|
> The parameter names used for binding (e.g., `"api_key"`) must exactly match the
|
|
|
|
|
> parameter names defined in the tool's configuration within the Toolbox
|
|
|
|
|
> service.
|
|
|
|
|
|
|
|
|
|
> [!NOTE]
|
|
|
|
|
> You do not need to modify the tool's configuration in the Toolbox service to
|
|
|
|
|
> bind parameter values using the SDK.
|
|
|
|
|
|
|
|
|
|
#### Option A: Add Default Bound Parameters to a Client
|
|
|
|
|
|
|
|
|
|
You can add default tool level bound parameters to a client. Every tool / toolset
|
|
|
|
|
loaded by the client will have the bound parameter.
|
|
|
|
|
|
|
|
|
|
```go
|
|
|
|
|
|
|
|
|
|
ctx := context.Background()
|
|
|
|
|
|
|
|
|
|
client, err := core.NewToolboxClient("http://127.0.0.1:5000",
|
|
|
|
|
core.WithDefaultToolOptions(
|
|
|
|
|
core.WithBindParamString("param1", "value"),
|
|
|
|
|
),
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
boundTool, err := client.LoadTool("my-tool", ctx)
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
### Option B: Binding Parameters to a Loaded Tool
|
|
|
|
|
|
|
|
|
|
Bind values to a tool object *after* it has been loaded. This modifies the
|
|
|
|
|
specific tool instance.
|
|
|
|
|
|
|
|
|
|
```go
|
|
|
|
|
client, err := core.NewToolboxClient("http://127.0.0.1:5000")
|
|
|
|
|
|
|
|
|
|
tool, err := client.LoadTool("my-tool", ctx)
|
|
|
|
|
|
|
|
|
|
boundTool, err := tool.ToolFrom(
|
|
|
|
|
core.WithBindParamString("param1", "value"),
|
|
|
|
|
core.WithBindParamString("param2", "value")
|
|
|
|
|
)
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
### Option C: Binding Parameters While Loading Tools
|
|
|
|
|
|
|
|
|
|
Specify bound parameters directly when loading tools. This applies the binding
|
|
|
|
|
only to the tools loaded in that specific call.
|
|
|
|
|
|
|
|
|
|
```go
|
|
|
|
|
boundTool, err := client.LoadTool("my-tool", ctx, core.WithBindParamString("param", "value"))
|
|
|
|
|
|
|
|
|
|
// OR
|
|
|
|
|
|
|
|
|
|
boundTool, err := client.LoadToolset("", ctx, core.WithBindParamString("param", "value"))
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
> [!NOTE]
|
|
|
|
|
> Bound values during loading only affect the tools loaded in that call.
|
|
|
|
|
|
|
|
|
|
### Binding Dynamic Values
|
|
|
|
|
|
|
|
|
|
Instead of a static value, you can bind a parameter to a synchronous or
|
|
|
|
|
asynchronous function. This function will be called *each time* the tool is
|
|
|
|
|
invoked to dynamically determine the parameter's value at runtime.
|
|
|
|
|
Functions with the return type (data_type, error) can be provided.
|
|
|
|
|
|
|
|
|
|
```go
|
|
|
|
|
getDynamicValue := func() (string, error) { return "req-123", nil }
|
|
|
|
|
|
|
|
|
|
dynamicBoundTool, err := tool.ToolFrom(core.WithBindParamStringFunc("param", getDynamicValue))
|
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
> [!IMPORTANT]
|
|
|
|
|
> You don't need to modify tool configurations to bind parameter values.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
# Using with Orchestration Frameworks
|
|
|
|
|
|
|
|
|
|
To see how the MCP Toolbox Go SDK works with orchestration frameworks, check out the end-to-end examples in the [/samples/](https://github.com/googleapis/mcp-toolbox-sdk-go/tree/main/core/samples) folder.
|
|
|
|
|
|
|
|
|
|
Use the [tbgenkit package](https://github.com/googleapis/mcp-toolbox-sdk-go/tree/main/tbgenkit) to convert Toolbox Tools into Genkit compatible tools.
|
|
|
|
|
|
|
|
|
|
# Contributing
|
|
|
|
|
|
|
|
|
|
Contributions are welcome! Please refer to the [DEVELOPER.md](https://github.com/googleapis/mcp-toolbox-sdk-go/blob/main/DEVELOPER.md)
|
|
|
|
|
file for guidelines on how to set up a development environment and run tests.
|
|
|
|
|
|
|
|
|
|
# License
|
|
|
|
|
|
|
|
|
|
This project is licensed under the Apache License 2.0. See the
|
|
|
|
|
[LICENSE](https://github.com/googleapis/mcp-toolbox-sdk-go/blob/main/LICENSE) file for details.
|
|
|
|
|
|
|
|
|
|
# Support
|
|
|
|
|
|
|
|
|
|
If you encounter issues or have questions, check the existing [GitHub Issues](https://github.com/googleapis/genai-toolbox/issues) for the main Toolbox project.
|
|
|
|
|
|
|
|
|
|
## Samples for Reference
|
|
|
|
|
|
|
|
|
|
These samples demonstrate how to integrate the MCP Toolbox Go Core SDK with popular orchestration frameworks.
|
|
|
|
|
|
|
|
|
|
{{< tabpane persist=header >}}
|
|
|
|
|
|
|
|
|
|
{{< tab header="Google GenAI" lang="go" >}}
|
|
|
|
|
// This sample demonstrates integration with the standard Google GenAI framework.
|
|
|
|
|
package main
|
|
|
|
|
|
|
|
|
|
import (
|
|
|
|
|
"context"
|
|
|
|
|
"encoding/json"
|
|
|
|
|
"fmt"
|
|
|
|
|
"log"
|
|
|
|
|
"os"
|
|
|
|
|
|
|
|
|
|
"github.com/googleapis/mcp-toolbox-sdk-go/core"
|
|
|
|
|
"google.golang.org/genai"
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
// ConvertToGenaiTool translates a ToolboxTool into the genai.FunctionDeclaration format.
|
|
|
|
|
func ConvertToGenaiTool(toolboxTool *core.ToolboxTool) *genai.Tool {
|
|
|
|
|
|
|
|
|
|
inputschema, err := toolboxTool.InputSchema()
|
|
|
|
|
if err != nil {
|
|
|
|
|
return &genai.Tool{}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
var schema *genai.Schema
|
|
|
|
|
_ = json.Unmarshal(inputschema, &schema)
|
|
|
|
|
// First, create the function declaration.
|
|
|
|
|
funcDeclaration := &genai.FunctionDeclaration{
|
|
|
|
|
Name: toolboxTool.Name(),
|
|
|
|
|
Description: toolboxTool.Description(),
|
|
|
|
|
Parameters: schema,
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Then, wrap the function declaration in a genai.Tool struct.
|
|
|
|
|
return &genai.Tool{
|
|
|
|
|
FunctionDeclarations: []*genai.FunctionDeclaration{funcDeclaration},
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// printResponse extracts and prints the relevant parts of the model's response.
|
|
|
|
|
func printResponse(resp *genai.GenerateContentResponse) {
|
|
|
|
|
for _, cand := range resp.Candidates {
|
|
|
|
|
if cand.Content != nil {
|
|
|
|
|
for _, part := range cand.Content.Parts {
|
|
|
|
|
fmt.Println(part.Text)
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
func main() {
|
|
|
|
|
// Setup
|
|
|
|
|
ctx := context.Background()
|
|
|
|
|
apiKey := os.Getenv("GOOGLE_API_KEY")
|
|
|
|
|
toolboxURL := "http://localhost:5000"
|
|
|
|
|
|
|
|
|
|
// Initialize the Google GenAI client using the explicit ClientConfig.
|
|
|
|
|
client, err := genai.NewClient(ctx, &genai.ClientConfig{
|
|
|
|
|
APIKey: apiKey,
|
|
|
|
|
})
|
|
|
|
|
if err != nil {
|
|
|
|
|
log.Fatalf("Failed to create Google GenAI client: %v", err)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Initialize the MCP Toolbox client.
|
|
|
|
|
toolboxClient, err := core.NewToolboxClient(toolboxURL)
|
|
|
|
|
if err != nil {
|
|
|
|
|
log.Fatalf("Failed to create Toolbox client: %v", err)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Load the tools using the MCP Toolbox SDK.
|
|
|
|
|
tools, err := toolboxClient.LoadToolset("my-toolset", ctx)
|
|
|
|
|
if err != nil {
|
|
|
|
|
log.Fatalf("Failed to load tools: %v\nMake sure your Toolbox server is running and the tool is configured.", err)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
genAITools := make([]*genai.Tool, len(tools))
|
|
|
|
|
toolsMap := make(map[string]*core.ToolboxTool, len(tools))
|
|
|
|
|
|
|
|
|
|
for i, tool := range tools {
|
|
|
|
|
// Convert the tools into usable format
|
|
|
|
|
genAITools[i] = ConvertToGenaiTool(tool)
|
|
|
|
|
// Add tool to a map for lookup later
|
|
|
|
|
toolsMap[tool.Name()] = tool
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Set up the generative model with the available tool.
|
|
|
|
|
modelName := "gemini-2.0-flash"
|
|
|
|
|
|
|
|
|
|
query := "Find hotels in Basel with Basel in it's name and share the names with me"
|
|
|
|
|
|
|
|
|
|
// Create the initial content prompt for the model.
|
|
|
|
|
contents := []*genai.Content{
|
|
|
|
|
genai.NewContentFromText(query, genai.RoleUser),
|
|
|
|
|
}
|
|
|
|
|
config := &genai.GenerateContentConfig{
|
|
|
|
|
Tools: genAITools,
|
|
|
|
|
ToolConfig: &genai.ToolConfig{
|
|
|
|
|
FunctionCallingConfig: &genai.FunctionCallingConfig{
|
|
|
|
|
Mode: genai.FunctionCallingConfigModeAny,
|
|
|
|
|
},
|
|
|
|
|
},
|
|
|
|
|
}
|
|
|
|
|
genContentResp, _ := client.Models.GenerateContent(ctx, modelName, contents, config)
|
|
|
|
|
|
|
|
|
|
printResponse(genContentResp)
|
|
|
|
|
|
|
|
|
|
functionCalls := genContentResp.FunctionCalls()
|
|
|
|
|
if len(functionCalls) == 0 {
|
|
|
|
|
log.Println("No function call returned by the AI. The model likely answered directly.")
|
|
|
|
|
return
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Process the first function call (the example assumes one for simplicity).
|
|
|
|
|
fc := functionCalls[0]
|
|
|
|
|
log.Printf("--- Gemini requested function call: %s ---\n", fc.Name)
|
|
|
|
|
log.Printf("--- Arguments: %+v ---\n", fc.Args)
|
|
|
|
|
|
|
|
|
|
var toolResultString string
|
|
|
|
|
|
|
|
|
|
if fc.Name == "search-hotels-by-name" {
|
|
|
|
|
tool := toolsMap["search-hotels-by-name"]
|
|
|
|
|
toolResult, err := tool.Invoke(ctx, fc.Args)
|
|
|
|
|
toolResultString = fmt.Sprintf("%v", toolResult)
|
|
|
|
|
if err != nil {
|
|
|
|
|
log.Fatalf("Failed to execute tool '%s': %v", fc.Name, err)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
} else {
|
|
|
|
|
log.Println("LLM did not request our tool")
|
|
|
|
|
}
|
|
|
|
|
resultContents := []*genai.Content{
|
|
|
|
|
genai.NewContentFromText("The tool returned this result, share it with the user based of their previous querys"+toolResultString, genai.RoleUser),
|
|
|
|
|
}
|
|
|
|
|
finalResponse, err := client.Models.GenerateContent(ctx, modelName, resultContents, &genai.GenerateContentConfig{})
|
|
|
|
|
if err != nil {
|
|
|
|
|
log.Fatalf("Error calling GenerateContent (with function result): %v", err)
|
|
|
|
|
}
|
|
|
|
|
log.Println("=== Final Response from Model (after processing function result) ===")
|
|
|
|
|
printResponse(finalResponse)
|
|
|
|
|
|
|
|
|
|
}
|
|
|
|
|
{{< /tab >}}
|
|
|
|
|
|
|
|
|
|
{{< tab header="LangChain Go" lang="go" >}}
|
|
|
|
|
// This sample demonstrates how to use Toolbox tools as function definitions in LangChain Go.
|
|
|
|
|
package main
|
|
|
|
|
|
|
|
|
|
import (
|
|
|
|
|
"context"
|
|
|
|
|
"encoding/json"
|
|
|
|
|
"fmt"
|
|
|
|
|
"log"
|
|
|
|
|
"os"
|
|
|
|
|
|
|
|
|
|
"github.com/googleapis/mcp-toolbox-sdk-go/core"
|
|
|
|
|
"github.com/tmc/langchaingo/llms"
|
|
|
|
|
"github.com/tmc/langchaingo/llms/googleai"
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
// ConvertToLangchainTool converts a generic core.ToolboxTool into a LangChainGo llms.Tool.
|
|
|
|
|
func ConvertToLangchainTool(toolboxTool *core.ToolboxTool) llms.Tool {
|
|
|
|
|
|
|
|
|
|
// Fetch the tool's input schema
|
|
|
|
|
inputschema, err := toolboxTool.InputSchema()
|
|
|
|
|
if err != nil {
|
|
|
|
|
return llms.Tool{}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
var paramsSchema map[string]any
|
|
|
|
|
_ = json.Unmarshal(inputschema, ¶msSchema)
|
|
|
|
|
|
|
|
|
|
// Convert into LangChain's llms.Tool
|
|
|
|
|
return llms.Tool{
|
|
|
|
|
Type: "function",
|
|
|
|
|
Function: &llms.FunctionDefinition{
|
|
|
|
|
Name: toolboxTool.Name(),
|
|
|
|
|
Description: toolboxTool.Description(),
|
|
|
|
|
Parameters: paramsSchema,
|
|
|
|
|
},
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
func main() {
|
|
|
|
|
genaiKey := os.Getenv("GOOGLE_API_KEY")
|
|
|
|
|
toolboxURL := "http://localhost:5000"
|
|
|
|
|
ctx := context.Background()
|
|
|
|
|
|
|
|
|
|
// Initialize the Google AI client (LLM).
|
|
|
|
|
llm, err := googleai.New(ctx, googleai.WithAPIKey(genaiKey), googleai.WithDefaultModel("gemini-1.5-flash"))
|
|
|
|
|
if err != nil {
|
|
|
|
|
log.Fatalf("Failed to create Google AI client: %v", err)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Initialize the MCP Toolbox client.
|
|
|
|
|
toolboxClient, err := core.NewToolboxClient(toolboxURL)
|
|
|
|
|
if err != nil {
|
|
|
|
|
log.Fatalf("Failed to create Toolbox client: %v", err)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Load the tools using the MCP Toolbox SDK.
|
|
|
|
|
tools, err := toolboxClient.LoadToolset("my-toolset", ctx)
|
|
|
|
|
if err != nil {
|
|
|
|
|
log.Fatalf("Failed to load tools: %v\nMake sure your Toolbox server is running and the tool is configured.", err)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
toolsMap := make(map[string]*core.ToolboxTool, len(tools))
|
|
|
|
|
|
|
|
|
|
langchainTools := make([]llms.Tool, len(tools))
|
|
|
|
|
for i, tool := range tools {
|
|
|
|
|
// Convert the loaded ToolboxTools into the format LangChainGo requires.
|
|
|
|
|
langchainTools[i] = ConvertToLangchainTool(tool)
|
|
|
|
|
// Add tool to a map for lookup later
|
|
|
|
|
toolsMap[tool.Name()] = tool
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Start the conversation history.
|
|
|
|
|
messageHistory := []llms.MessageContent{
|
|
|
|
|
llms.TextParts(llms.ChatMessageTypeHuman, "Find hotels in Basel with Basel in it's name."),
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Make the first call to the LLM, making it aware of the tool.
|
|
|
|
|
resp, err := llm.GenerateContent(ctx, messageHistory, llms.WithTools(langchainTools))
|
|
|
|
|
if err != nil {
|
|
|
|
|
log.Fatalf("LLM call failed: %v", err)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Add the model's response (which should be a tool call) to the history.
|
|
|
|
|
respChoice := resp.Choices[0]
|
|
|
|
|
assistantResponse := llms.TextParts(llms.ChatMessageTypeAI, respChoice.Content)
|
|
|
|
|
for _, tc := range respChoice.ToolCalls {
|
|
|
|
|
assistantResponse.Parts = append(assistantResponse.Parts, tc)
|
|
|
|
|
}
|
|
|
|
|
messageHistory = append(messageHistory, assistantResponse)
|
|
|
|
|
|
|
|
|
|
// Process each tool call requested by the model.
|
|
|
|
|
for _, tc := range respChoice.ToolCalls {
|
|
|
|
|
toolName := tc.FunctionCall.Name
|
|
|
|
|
|
|
|
|
|
switch tc.FunctionCall.Name {
|
|
|
|
|
case "search-hotels-by-name":
|
|
|
|
|
var args map[string]any
|
|
|
|
|
if err := json.Unmarshal([]byte(tc.FunctionCall.Arguments), &args); err != nil {
|
|
|
|
|
log.Fatalf("Failed to unmarshal arguments for tool '%s': %v", toolName, err)
|
|
|
|
|
}
|
|
|
|
|
tool := toolsMap["search-hotels-by-name"]
|
|
|
|
|
toolResult, err := tool.Invoke(ctx, args)
|
|
|
|
|
if err != nil {
|
|
|
|
|
log.Fatalf("Failed to execute tool '%s': %v", toolName, err)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Create the tool call response message and add it to the history.
|
|
|
|
|
toolResponse := llms.MessageContent{
|
|
|
|
|
Role: llms.ChatMessageTypeTool,
|
|
|
|
|
Parts: []llms.ContentPart{
|
|
|
|
|
llms.ToolCallResponse{
|
|
|
|
|
Name: toolName,
|
|
|
|
|
Content: fmt.Sprintf("%v", toolResult),
|
|
|
|
|
},
|
|
|
|
|
},
|
|
|
|
|
}
|
|
|
|
|
messageHistory = append(messageHistory, toolResponse)
|
|
|
|
|
default:
|
|
|
|
|
log.Fatalf("got unexpected function call: %v", tc.FunctionCall.Name)
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Final LLM Call for Natural Language Response
|
|
|
|
|
log.Println("Sending tool response back to LLM for a final answer...")
|
|
|
|
|
|
|
|
|
|
// Call the LLM again with the updated history, which now includes the tool's result.
|
|
|
|
|
finalResp, err := llm.GenerateContent(ctx, messageHistory)
|
|
|
|
|
if err != nil {
|
|
|
|
|
log.Fatalf("Final LLM call failed: %v", err)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Display the Result
|
|
|
|
|
fmt.Println("\n======================================")
|
|
|
|
|
fmt.Println("Final Response from LLM:")
|
|
|
|
|
fmt.Println(finalResp.Choices[0].Content)
|
|
|
|
|
fmt.Println("======================================")
|
|
|
|
|
}
|
|
|
|
|
{{< /tab >}}
|
|
|
|
|
|
|
|
|
|
{{< tab header="OpenAI Go" lang="go" >}}
|
|
|
|
|
// This sample demonstrates integration with the OpenAI Go client.
|
|
|
|
|
package main
|
|
|
|
|
|
|
|
|
|
import (
|
|
|
|
|
"context"
|
|
|
|
|
"encoding/json"
|
|
|
|
|
"fmt"
|
|
|
|
|
"log"
|
|
|
|
|
|
|
|
|
|
"github.com/googleapis/mcp-toolbox-sdk-go/core"
|
|
|
|
|
openai "github.com/openai/openai-go"
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
// ConvertToOpenAITool converts a ToolboxTool into the go-openai library's Tool format.
|
|
|
|
|
func ConvertToOpenAITool(toolboxTool *core.ToolboxTool) openai.ChatCompletionToolParam {
|
|
|
|
|
// Get the input schema
|
|
|
|
|
jsonSchemaBytes, err := toolboxTool.InputSchema()
|
|
|
|
|
if err != nil {
|
|
|
|
|
return openai.ChatCompletionToolParam{}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Unmarshal the JSON bytes into FunctionParameters
|
|
|
|
|
var paramsSchema openai.FunctionParameters
|
|
|
|
|
if err := json.Unmarshal(jsonSchemaBytes, ¶msSchema); err != nil {
|
|
|
|
|
return openai.ChatCompletionToolParam{}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Create and return the final tool parameter struct.
|
|
|
|
|
return openai.ChatCompletionToolParam{
|
|
|
|
|
Function: openai.FunctionDefinitionParam{
|
|
|
|
|
Name: toolboxTool.Name(),
|
|
|
|
|
Description: openai.String(toolboxTool.Description()),
|
|
|
|
|
Parameters: paramsSchema,
|
|
|
|
|
},
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
func main() {
|
|
|
|
|
// Setup
|
|
|
|
|
ctx := context.Background()
|
|
|
|
|
toolboxURL := "http://localhost:5000"
|
|
|
|
|
openAIClient := openai.NewClient()
|
|
|
|
|
|
|
|
|
|
// Initialize the MCP Toolbox client.
|
|
|
|
|
toolboxClient, err := core.NewToolboxClient(toolboxURL)
|
|
|
|
|
if err != nil {
|
|
|
|
|
log.Fatalf("Failed to create Toolbox client: %v", err)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Load the tools using the MCP Toolbox SDK.
|
|
|
|
|
tools, err := toolboxClient.LoadToolset("my-toolset", ctx)
|
|
|
|
|
if err != nil {
|
|
|
|
|
log.Fatalf("Failed to load tool : %v\nMake sure your Toolbox server is running and the tool is configured.", err)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
openAITools := make([]openai.ChatCompletionToolParam, len(tools))
|
|
|
|
|
toolsMap := make(map[string]*core.ToolboxTool, len(tools))
|
|
|
|
|
|
|
|
|
|
for i, tool := range tools {
|
|
|
|
|
// Convert the Toolbox tool into the openAI FunctionDeclaration format.
|
|
|
|
|
openAITools[i] = ConvertToOpenAITool(tool)
|
|
|
|
|
// Add tool to a map for lookup later
|
|
|
|
|
toolsMap[tool.Name()] = tool
|
|
|
|
|
|
|
|
|
|
}
|
|
|
|
|
question := "Find hotels in Basel with Basel in it's name "
|
|
|
|
|
|
|
|
|
|
params := openai.ChatCompletionNewParams{
|
|
|
|
|
Messages: []openai.ChatCompletionMessageParamUnion{
|
|
|
|
|
openai.UserMessage(question),
|
|
|
|
|
},
|
|
|
|
|
Tools: openAITools,
|
|
|
|
|
Seed: openai.Int(0),
|
|
|
|
|
Model: openai.ChatModelGPT4o,
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// Make initial chat completion request
|
|
|
|
|
completion, err := openAIClient.Chat.Completions.New(ctx, params)
|
|
|
|
|
if err != nil {
|
|
|
|
|
panic(err)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
toolCalls := completion.Choices[0].Message.ToolCalls
|
|
|
|
|
|
|
|
|
|
// Return early if there are no tool calls
|
|
|
|
|
if len(toolCalls) == 0 {
|
|
|
|
|
fmt.Printf("No function call")
|
|
|
|
|
return
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
// If there is a was a function call, continue the conversation
|
|
|
|
|
params.Messages = append(params.Messages, completion.Choices[0].Message.ToParam())
|
|
|
|
|
for _, toolCall := range toolCalls {
|
|
|
|
|
if toolCall.Function.Name == "search-hotels-by-name" {
|
|
|
|
|
// Extract the location from the function call arguments
|
|
|
|
|
var args map[string]interface{}
|
|
|
|
|
tool := toolsMap["search-hotels-by-name"]
|
|
|
|
|
err := json.Unmarshal([]byte(toolCall.Function.Arguments), &args)
|
|
|
|
|
if err != nil {
|
|
|
|
|
panic(err)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
result, err := tool.Invoke(ctx, args)
|
|
|
|
|
if err != nil {
|
|
|
|
|
log.Fatal("Could not invoke tool", err)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
params.Messages = append(params.Messages, openai.ToolMessage(result.(string), toolCall.ID))
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
completion, err = openAIClient.Chat.Completions.New(ctx, params)
|
|
|
|
|
if err != nil {
|
|
|
|
|
panic(err)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
fmt.Println(completion.Choices[0].Message.Content)
|
|
|
|
|
}
|
|
|
|
|
{{< /tab >}}
|
|
|
|
|
|
|
|
|
|
{{< /tabpane >}}
|
