API Integration
Integrate this MCP server into your applications.
Get your API Key
You'll need to login and generate a Smithery API key to connect to this server.
Installation
Install the official MCP SDKs using npm:
bash
npm install @modelcontextprotocol/sdk @smithery/sdkTypeScript SDK
typescript
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp.js"
import { createSmitheryUrl } from "@smithery/sdk"
const config = {
"vertexAiModelId": "gemini-2.5-pro-exp-03-25",
"googleCloudProject": "string",
"vertexAiMaxRetries": 3,
"googleCloudLocation": "string",
"vertexAiTemperature": 0,
"vertexAiRetryDelayMs": 1000,
"vertexAiUseStreaming": true,
"vertexAiMaxOutputTokens": 65535,
"googleApplicationCredentials": "string"
}
const serverUrl = createSmitheryUrl("https://server.smithery.ai/@shariqriazz/vertex-ai-mcp-server", config, "your-smithery-api-key")
const transport = new StreamableHTTPClientTransport(serverUrl)
// Create MCP client
import { Client } from "@modelcontextprotocol/sdk/client/index.js"
const client = new Client({
name: "Test client",
version: "1.0.0"
})
await client.connect(transport)
// Use the server tools with your LLM application
const tools = await client.listTools()
console.log(`Available tools: ${tools.map(t => t.name).join(", ")}`)
Configuration Schema
Full JSON Schema for server configuration:
json
{
"type": "object",
"required": [
"googleCloudProject",
"googleCloudLocation"
],
"properties": {
"vertexAiModelId": {
"type": "string",
"default": "gemini-2.5-pro-exp-03-25",
"description": "Vertex AI Model ID"
},
"googleCloudProject": {
"type": "string",
"description": "Google Cloud Project ID"
},
"vertexAiMaxRetries": {
"type": "number",
"default": 3,
"description": "Max retry attempts"
},
"googleCloudLocation": {
"type": "string",
"description": "Google Cloud Location"
},
"vertexAiTemperature": {
"type": "number",
"default": 0,
"description": "Temperature for model"
},
"vertexAiRetryDelayMs": {
"type": "number",
"default": 1000,
"description": "Delay between retries in ms"
},
"vertexAiUseStreaming": {
"type": "boolean",
"default": true,
"description": "Whether to use streaming"
},
"vertexAiMaxOutputTokens": {
"type": "number",
"default": 65535,
"description": "Max output tokens"
},
"googleApplicationCredentials": {
"type": "string",
"description": "Path to service account key JSON"
}
}
}