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25
docs/en/sdks/JS-sdk/_index.md
Normal file
25
docs/en/sdks/JS-sdk/_index.md
Normal file
@@ -0,0 +1,25 @@
|
||||
---
|
||||
title: "JS SDK"
|
||||
type: docs
|
||||
weight: 7
|
||||
description: >
|
||||
JS SDKs to connect to the MCP Toolbox server.
|
||||
---
|
||||
|
||||
|
||||
## Overview
|
||||
|
||||
The MCP Toolbox service provides a centralized way to manage and expose tools
|
||||
(like API connectors, database query tools, etc.) for use by GenAI applications.
|
||||
|
||||
These JS SDKs act as clients for that service. They handle the communication needed to:
|
||||
|
||||
* Fetch tool definitions from your running Toolbox instance.
|
||||
* Provide convenient JS objects or functions representing those tools.
|
||||
* Invoke the tools (calling the underlying APIs/services configured in Toolbox).
|
||||
* Handle authentication and parameter binding as needed.
|
||||
|
||||
By using these SDKs, you can easily leverage your Toolbox-managed tools directly
|
||||
within your JS applications or AI orchestration frameworks.
|
||||
|
||||
[Github](https://github.com/googleapis/mcp-toolbox-sdk-js)
|
||||
@@ -1,15 +0,0 @@
|
||||
---
|
||||
title: "Go SDK"
|
||||
weight: 2
|
||||
description: Go lang client SDK
|
||||
icon: fa-brands fa-golang
|
||||
manualLink: "https://github.com/googleapis/mcp-toolbox-sdk-go"
|
||||
manualLinkTarget: _blank
|
||||
---
|
||||
|
||||
<html>
|
||||
<head>
|
||||
<link rel="canonical" href="https://github.com/googleapis/mcp-toolbox-sdk-go"/>
|
||||
<meta http-equiv="refresh" content="0;url=https://github.com/googleapis/mcp-toolbox-sdk-go"/>
|
||||
</head>
|
||||
</html>
|
||||
114
docs/en/sdks/go-sdk/_index.md
Normal file
114
docs/en/sdks/go-sdk/_index.md
Normal file
@@ -0,0 +1,114 @@
|
||||
---
|
||||
title: "Go SDK"
|
||||
type: docs
|
||||
weight: 7
|
||||
description: >
|
||||
Go SDKs to connect to the MCP Toolbox server.
|
||||
---
|
||||
|
||||
|
||||
## Overview
|
||||
|
||||
|
||||
|
||||
# MCP Toolbox SDKs for Go
|
||||
|
||||
[](https://opensource.org/licenses/Apache-2.0)
|
||||
[](https://googleapis.github.io/genai-toolbox/)
|
||||
[](https://discord.gg/Dmm69peqjh)
|
||||
[](https://medium.com/@mcp_toolbox)
|
||||
[](https://goreportcard.com/report/github.com/googleapis/mcp-toolbox-sdk-go)
|
||||
[](https://img.shields.io/github/v/release/googleapis/mcp-toolbox-sdk-go)
|
||||
[](https://img.shields.io/github/go-mod/go-version/googleapis/mcp-toolbox-sdk-go)
|
||||
|
||||
This repository contains the Go SDK designed to seamlessly integrate the
|
||||
functionalities of the [MCP
|
||||
Toolbox](https://github.com/googleapis/genai-toolbox) into your Gen AI
|
||||
applications. The SDK allow you to load tools defined in Toolbox and use them
|
||||
as standard Go tools within popular orchestration frameworks
|
||||
or your custom code.
|
||||
|
||||
This simplifies the process of incorporating external functionalities (like
|
||||
Databases or APIs) managed by Toolbox into your GenAI applications.
|
||||
|
||||
<!-- TOC -->
|
||||
|
||||
- [Overview](#overview)
|
||||
- [Which Package Should I Use?](#which-package-should-i-use)
|
||||
- [Available Packages](#available-packages)
|
||||
- [Getting Started](#getting-started)
|
||||
|
||||
<!-- /TOC -->
|
||||
|
||||
## Overview
|
||||
|
||||
The MCP Toolbox service provides a centralized way to manage and expose tools
|
||||
(like API connectors, database query tools, etc.) for use by GenAI applications.
|
||||
|
||||
The Go SDK act as clients for that service. They handle the communication needed to:
|
||||
|
||||
* Fetch tool definitions from your running Toolbox instance.
|
||||
* Provide convenient Go structs representing those tools.
|
||||
* Invoke the tools (calling the underlying APIs/services configured in Toolbox).
|
||||
* Handle authentication and parameter binding as needed.
|
||||
|
||||
By using the SDK, you can easily leverage your Toolbox-managed tools directly
|
||||
within your Go applications or AI orchestration frameworks.
|
||||
|
||||
## Which Package Should I Use?
|
||||
|
||||
Choosing the right package depends on how you are building your application:
|
||||
|
||||
- [`core`](https://github.com/googleapis/mcp-toolbox-sdk-go/tree/main/core):
|
||||
This is a framework agnostic way to connect the tools to popular frameworks
|
||||
like Google GenAI, LangChain, etc.
|
||||
|
||||
- [`tbadk`](https://github.com/googleapis/mcp-toolbox-sdk-go/tree/main/tbadk):
|
||||
This package provides a way to connect tools to ADK Go.
|
||||
|
||||
- [`tbgenkit`](https://github.com/googleapis/mcp-toolbox-sdk-go/tree/main/tbgenkit):
|
||||
This package provides a functionality to convert the Tool fetched using the core package
|
||||
into a Genkit Go compatible tool.
|
||||
|
||||
## Available Packages
|
||||
|
||||
This repository hosts the following Go packages. See the package-specific
|
||||
README for detailed installation and usage instructions:
|
||||
|
||||
| Package | Target Use Case | Integration | Path | Details (README) |
|
||||
| :------ | :----------| :---------- | :---------------------- | :---------- |
|
||||
| `core` | Framework-agnostic / Custom applications | Use directly / Custom | `core/` | 📄 [View README](https://github.com/googleapis/mcp-toolbox-sdk-go/blob/main/core/README.md) |
|
||||
| `tbadk` | ADK Go | Use directly | `tbadk/` | 📄 [View README](https://github.com/googleapis/mcp-toolbox-sdk-go/blob/main/tbadk/README.md) |
|
||||
| `tbgenkit` | Genkit Go | Along with core | `tbgenkit/` | 📄 [View README](https://github.com/googleapis/mcp-toolbox-sdk-go/blob/main/tbgenkit/README.md) |
|
||||
|
||||
## Getting Started
|
||||
|
||||
To get started using Toolbox tools with an application, follow these general steps:
|
||||
|
||||
1. **Set up and Run the Toolbox Service:**
|
||||
|
||||
Before using the SDKs, you need the MCP Toolbox server running. Follow
|
||||
the instructions here: [**Toolbox Getting Started
|
||||
Guide**](https://github.com/googleapis/genai-toolbox?tab=readme-ov-file#getting-started)
|
||||
|
||||
2. **Install the Appropriate SDK:**
|
||||
|
||||
Choose the package based on your needs (see "[Which Package Should I Use?](#which-package-should-i-use)" above)
|
||||
Use this command to install the SDK module
|
||||
|
||||
```bash
|
||||
# For the core, framework-agnostic SDK
|
||||
go get github.com/googleapis/mcp-toolbox-sdk-go
|
||||
```
|
||||
|
||||
3. **Use the SDK:**
|
||||
|
||||
Consult the README for your chosen package (linked in the "[Available
|
||||
Packages](#available-packages)" section above) for detailed instructions on
|
||||
how to connect the client, load tool definitions, invoke tools, configure
|
||||
authentication/binding, and integrate them into your application or
|
||||
framework.
|
||||
|
||||
[Github](https://github.com/googleapis/mcp-toolbox-sdk-go)
|
||||
7
docs/en/sdks/go-sdk/samples/_index.md
Normal file
7
docs/en/sdks/go-sdk/samples/_index.md
Normal file
@@ -0,0 +1,7 @@
|
||||
---
|
||||
title: "Samples"
|
||||
type: docs
|
||||
weight: 20
|
||||
---
|
||||
## Go SDK Samples
|
||||
Explore how to integrate the Go SDK with various orchestration frameworks.
|
||||
114
docs/en/sdks/go-sdk/samples/go-adk.md
Normal file
114
docs/en/sdks/go-sdk/samples/go-adk.md
Normal file
@@ -0,0 +1,114 @@
|
||||
---
|
||||
title: "ADK Integration"
|
||||
linkTitle: "Go ADK"
|
||||
type: docs
|
||||
weight: 1
|
||||
---
|
||||
|
||||
This sample contains a complete example on how to integrate MCP Toolbox Go SDK with ADK Go using the tbadk package.
|
||||
|
||||
```go
|
||||
package main
|
||||
|
||||
import (
|
||||
"context"
|
||||
"fmt"
|
||||
"log"
|
||||
"os"
|
||||
|
||||
"github.com/googleapis/mcp-toolbox-sdk-go/tbadk"
|
||||
"google.golang.org/adk/agent"
|
||||
"google.golang.org/adk/agent/llmagent"
|
||||
"google.golang.org/adk/model/gemini"
|
||||
"google.golang.org/adk/runner"
|
||||
"google.golang.org/adk/session"
|
||||
"google.golang.org/adk/tool"
|
||||
"google.golang.org/genai"
|
||||
)
|
||||
|
||||
func main() {
|
||||
genaiKey := os.Getenv("GEMINI_API_KEY")
|
||||
toolboxURL := "http://localhost:5000"
|
||||
ctx := context.Background()
|
||||
|
||||
// Initialize MCP Toolbox client
|
||||
toolboxClient, err := tbadk.NewToolboxClient(toolboxURL)
|
||||
if err != nil {
|
||||
log.Fatalf("Failed to create MCP Toolbox client: %v", err)
|
||||
}
|
||||
|
||||
toolsetName := "my-toolset"
|
||||
toolset, err := toolboxClient.LoadToolset(toolsetName, ctx)
|
||||
if err != nil {
|
||||
log.Fatalf("Failed to load MCP toolset '%s': %v\nMake sure your Toolbox server is running.", toolsetName, err)
|
||||
}
|
||||
|
||||
// Create Gemini model
|
||||
model, err := gemini.NewModel(ctx, "gemini-2.5-flash", &genai.ClientConfig{
|
||||
APIKey: genaiKey,
|
||||
})
|
||||
if err != nil {
|
||||
log.Fatalf("Failed to create model: %v", err)
|
||||
}
|
||||
|
||||
tools := make([]tool.Tool, len(toolset))
|
||||
for i := range toolset {
|
||||
tools[i] = &toolset[i]
|
||||
}
|
||||
|
||||
llmagent, err := llmagent.New(llmagent.Config{
|
||||
Name: "hotel_assistant",
|
||||
Model: model,
|
||||
Description: "Agent to answer questions about hotels.",
|
||||
Tools: tools,
|
||||
})
|
||||
if err != nil {
|
||||
log.Fatalf("Failed to create agent: %v", err)
|
||||
}
|
||||
|
||||
appName := "hotel_assistant"
|
||||
userID := "user-123"
|
||||
|
||||
sessionService := session.InMemoryService()
|
||||
resp, err := sessionService.Create(ctx, &session.CreateRequest{
|
||||
AppName: appName,
|
||||
UserID: userID,
|
||||
})
|
||||
if err != nil {
|
||||
log.Fatalf("Failed to create the session service: %v", err)
|
||||
}
|
||||
session := resp.Session
|
||||
|
||||
r, err := runner.New(runner.Config{
|
||||
AppName: appName,
|
||||
Agent: llmagent,
|
||||
SessionService: sessionService,
|
||||
})
|
||||
if err != nil {
|
||||
log.Fatalf("Failed to create runner: %v", err)
|
||||
}
|
||||
|
||||
query := "Find hotels with Basel in its name."
|
||||
|
||||
fmt.Println(query)
|
||||
userMsg := genai.NewContentFromText(query, genai.RoleUser)
|
||||
|
||||
streamingMode := agent.StreamingModeSSE
|
||||
for event, err := range r.Run(ctx, userID, session.ID(), userMsg, agent.RunConfig{
|
||||
StreamingMode: streamingMode,
|
||||
}) {
|
||||
if err != nil {
|
||||
fmt.Printf("\nAGENT_ERROR: %v\n", err)
|
||||
} else {
|
||||
if event.LLMResponse.Content != nil {
|
||||
for _, p := range event.LLMResponse.Content.Parts {
|
||||
if streamingMode != agent.StreamingModeSSE || event.LLMResponse.Partial {
|
||||
fmt.Print(p.Text)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
fmt.Println()
|
||||
}
|
||||
```
|
||||
150
docs/en/sdks/go-sdk/samples/go-genai.md
Normal file
150
docs/en/sdks/go-sdk/samples/go-genai.md
Normal file
@@ -0,0 +1,150 @@
|
||||
---
|
||||
title: "GenAI Integration"
|
||||
linkTitle: "Go GenAI"
|
||||
type: docs
|
||||
weight: 1
|
||||
---
|
||||
|
||||
This sample contains a complete example on how to integrate MCP Toolbox Go Core SDK with the Go GenAI SDK.
|
||||
|
||||
```go
|
||||
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)
|
||||
|
||||
}
|
||||
```
|
||||
71
docs/en/sdks/go-sdk/samples/go-genkit.md
Normal file
71
docs/en/sdks/go-sdk/samples/go-genkit.md
Normal file
@@ -0,0 +1,71 @@
|
||||
---
|
||||
title: "Genkit Integration"
|
||||
linkTitle: "Go Genkit"
|
||||
type: docs
|
||||
weight: 1
|
||||
---
|
||||
|
||||
This sample contains a complete example on how to integrate MCP Toolbox Go SDK with Genkit Go using the tbgenkit package.
|
||||
|
||||
```go
|
||||
package main
|
||||
|
||||
import (
|
||||
"context"
|
||||
"fmt"
|
||||
"log"
|
||||
|
||||
"github.com/googleapis/mcp-toolbox-sdk-go/core"
|
||||
"github.com/googleapis/mcp-toolbox-sdk-go/tbgenkit"
|
||||
|
||||
"github.com/firebase/genkit/go/ai"
|
||||
"github.com/firebase/genkit/go/genkit"
|
||||
"github.com/firebase/genkit/go/plugins/googlegenai"
|
||||
)
|
||||
|
||||
func main() {
|
||||
ctx := context.Background()
|
||||
toolboxClient, err := core.NewToolboxClient("http://127.0.0.1:5000")
|
||||
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)
|
||||
}
|
||||
|
||||
// Initialize genkit
|
||||
g := genkit.Init(ctx,
|
||||
genkit.WithPlugins(&googlegenai.GoogleAI{}),
|
||||
genkit.WithDefaultModel("googleai/gemini-1.5-flash"),
|
||||
)
|
||||
|
||||
// Convert your tool to a Genkit tool.
|
||||
genkitTools := make([]ai.Tool, len(tools))
|
||||
for i, tool := range tools {
|
||||
newTool, err := tbgenkit.ToGenkitTool(tool, g)
|
||||
if err != nil {
|
||||
log.Fatalf("Failed to convert tool: %v\n", err)
|
||||
}
|
||||
genkitTools[i] = newTool
|
||||
}
|
||||
|
||||
toolRefs := make([]ai.ToolRef, len(genkitTools))
|
||||
|
||||
for i, tool := range genkitTools {
|
||||
toolRefs[i] = tool
|
||||
}
|
||||
|
||||
// Generate llm response using prompts and tools.
|
||||
resp, err := genkit.Generate(ctx, g,
|
||||
ai.WithPrompt("Find hotels in Basel with Basel in it's name."),
|
||||
ai.WithTools(toolRefs...),
|
||||
)
|
||||
if err != nil {
|
||||
log.Fatalf("%v\n", err)
|
||||
}
|
||||
fmt.Println(resp.Text())
|
||||
}
|
||||
```
|
||||
147
docs/en/sdks/go-sdk/samples/go-langchain.md
Normal file
147
docs/en/sdks/go-sdk/samples/go-langchain.md
Normal file
@@ -0,0 +1,147 @@
|
||||
---
|
||||
title: "Langchain Integration"
|
||||
linkTitle: "Go Langchain"
|
||||
type: docs
|
||||
weight: 1
|
||||
---
|
||||
|
||||
This sample contains a complete example on how to integrate MCP Toolbox Go Core SDK with LangChain Go.
|
||||
|
||||
```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("======================================")
|
||||
}
|
||||
```
|
||||
128
docs/en/sdks/go-sdk/samples/go-openai.md
Normal file
128
docs/en/sdks/go-sdk/samples/go-openai.md
Normal file
@@ -0,0 +1,128 @@
|
||||
---
|
||||
title: "OpenAI Integration"
|
||||
linkTitle: "Go OpenAI"
|
||||
type: docs
|
||||
weight: 1
|
||||
---
|
||||
|
||||
This sample contains a complete example on how to integrate MCP Toolbox Go Core SDK with the OpenAI Go SDK.
|
||||
|
||||
```go
|
||||
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)
|
||||
}
|
||||
```
|
||||
@@ -1,15 +0,0 @@
|
||||
---
|
||||
title: "JS SDK"
|
||||
weight: 2
|
||||
description: Javascript client SDK
|
||||
icon: fa-brands fa-node-js
|
||||
manualLink: "https://github.com/googleapis/mcp-toolbox-sdk-js"
|
||||
manualLinkTarget: _blank
|
||||
---
|
||||
|
||||
<html>
|
||||
<head>
|
||||
<link rel="canonical" href="https://github.com/googleapis/mcp-toolbox-sdk-js"/>
|
||||
<meta http-equiv="refresh" content="0;url=https://github.com/googleapis/mcp-toolbox-sdk-js"/>
|
||||
</head>
|
||||
</html>
|
||||
@@ -1,15 +0,0 @@
|
||||
---
|
||||
title: "Python SDK"
|
||||
weight: 2
|
||||
description: Python client SDK
|
||||
icon: fa-brands fa-python
|
||||
manualLink: "https://github.com/googleapis/mcp-toolbox-sdk-python"
|
||||
manualLinkTarget: _blank
|
||||
---
|
||||
|
||||
<html>
|
||||
<head>
|
||||
<link rel="canonical" href="https://github.com/googleapis/mcp-toolbox-sdk-python"/>
|
||||
<meta http-equiv="refresh" content="0;url=https://github.com/googleapis/mcp-toolbox-sdk-python"/>
|
||||
</head>
|
||||
</html>
|
||||
25
docs/en/sdks/python-sdk/_index.md
Normal file
25
docs/en/sdks/python-sdk/_index.md
Normal file
@@ -0,0 +1,25 @@
|
||||
---
|
||||
title: "Python SDK"
|
||||
type: docs
|
||||
weight: 7
|
||||
description: >
|
||||
Python SDKs to connect to the MCP Toolbox server.
|
||||
---
|
||||
|
||||
|
||||
## Overview
|
||||
|
||||
The MCP Toolbox service provides a centralized way to manage and expose tools
|
||||
(like API connectors, database query tools, etc.) for use by GenAI applications.
|
||||
|
||||
These Python SDKs act as clients for that service. They handle the communication needed to:
|
||||
|
||||
* Fetch tool definitions from your running Toolbox instance.
|
||||
* Provide convenient Python objects or functions representing those tools.
|
||||
* Invoke the tools (calling the underlying APIs/services configured in Toolbox).
|
||||
* Handle authentication and parameter binding as needed.
|
||||
|
||||
By using these SDKs, you can easily leverage your Toolbox-managed tools directly
|
||||
within your Python applications or AI orchestration frameworks.
|
||||
|
||||
[Github](https://github.com/googleapis/mcp-toolbox-sdk-python)
|
||||
Reference in New Issue
Block a user