Vertex AI Vector Search MCP Server for Mastra AI 6 tools — connect in under 2 minutes
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Vertex AI Vector Search through the Vinkius and Mastra agents discover all tools automatically — type-safe, streaming-ready, and deployable anywhere Node.js runs.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";
async function main() {
// Your Vinkius token — get it at cloud.vinkius.com
const mcpClient = await createMCPClient({
servers: {
"vertex-ai-vector-search": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "Vertex AI Vector Search Agent",
instructions:
"You help users interact with Vertex AI Vector Search " +
"using 6 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with Vertex AI Vector Search?"
);
console.log(result.text);
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Vertex AI Vector Search MCP Server
Plug the sheer matching scale of Google Cloud's Vertex AI Vector Search directly into your intelligent IDE or conversational agent. Unleash low-latency nearest neighbor lookups across billion-scale embedding structures without navigating Cloud Console interfaces.
Mastra's agent abstraction provides a clean separation between LLM logic and Vertex AI Vector Search tool infrastructure. Connect 6 tools through the Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution — deployable to any Node.js host in one command.
What you can do
- Massive Semantic Extraction — Prompt your agent to formulate query vectors and blast them at your specialized Cloud endpoints. It instantly retrieves identical geometric text boundaries (nearest neighbors) to ground LLM contexts powerfully.
- Index Operations — Gain total situational awareness over your massive datasets. Command the bot to list your provisioned Vector Indexes, verifying dimensionality, configuration updates, and current active states within seconds.
- Endpoint Monitoring — List active network endpoints scaling your specific RAG applications. Determine clearly which underlying deployed index iterations are currently receiving production traffic without digging through IAM screens.
- Operation Tracking — Spun up a multi-terabyte index build? Query the cloud queue using chat to review persistent long-running task timelines from your primary editor.
The Vertex AI Vector Search MCP Server exposes 6 tools through the Vinkius. Connect it to Mastra AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Vertex AI Vector Search to Mastra AI via MCP
Follow these steps to integrate the Vertex AI Vector Search MCP Server with Mastra AI.
Install dependencies
Run npm install @mastra/core @mastra/mcp @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.ts and run with npx tsx agent.ts
Explore tools
Mastra discovers 6 tools from Vertex AI Vector Search via MCP
Why Use Mastra AI with the Vertex AI Vector Search MCP Server
Mastra AI provides unique advantages when paired with Vertex AI Vector Search through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure — add Vertex AI Vector Search without touching business code
Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
TypeScript-native: full type inference for every Vertex AI Vector Search tool response with IDE autocomplete and compile-time checks
One-command deployment to any Node.js host — Vercel, Railway, Fly.io, or your own infrastructure
Vertex AI Vector Search + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the Vertex AI Vector Search MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query Vertex AI Vector Search, process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed Vertex AI Vector Search as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query Vertex AI Vector Search on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using Vertex AI Vector Search tools alongside other MCP servers
Vertex AI Vector Search MCP Tools for Mastra AI (6)
These 6 tools become available when you connect Vertex AI Vector Search to Mastra AI via MCP:
get_index_details
Retrieves metadata and configuration for a specific vector index
list_deployed_indexes
Lists all indexes deployed to a specific endpoint
list_index_endpoints
Lists all index endpoints in the project
list_vector_indexes
Lists all vector indexes in the Google Cloud project
list_vector_operations
Lists long-running operations related to vector indexes
search_nearest_neighbors
Provide the endpoint ID, deployed index ID, and a query vector as a JSON array. Performs a nearest neighbor vector similarity search
Example Prompts for Vertex AI Vector Search in Mastra AI
Ready-to-use prompts you can give your Mastra AI agent to start working with Vertex AI Vector Search immediately.
"List all our active vector indexes on the current GCP project."
"Check for any long-running vector deployment operations currently uncompleted."
"Find the 3 nearest neighbors mapping to endpoint '39xl' array index ID 'dep_30' using vector [-0.2, 0.5, 0.0]."
Troubleshooting Vertex AI Vector Search MCP Server with Mastra AI
Common issues when connecting Vertex AI Vector Search to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpVertex AI Vector Search + Mastra AI FAQ
Common questions about integrating Vertex AI Vector Search MCP Server with Mastra AI.
How does Mastra AI connect to MCP servers?
MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.Can Mastra agents use tools from multiple servers?
Does Mastra support workflow orchestration?
Connect Vertex AI Vector Search with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Vertex AI Vector Search to Mastra AI
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.