Zilliz Cloud MCP Server for Mastra AI 10 tools — connect in under 2 minutes
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Zilliz Cloud 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: {
"zilliz-cloud": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "Zilliz Cloud Agent",
instructions:
"You help users interact with Zilliz Cloud " +
"using 10 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with Zilliz Cloud?"
);
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 Zilliz Cloud MCP Server
Connect your Zilliz Cloud cluster to any AI agent to automate your vector database operations. This MCP server enables your agent to manage collections, insert data, and perform high-performance similarity searches directly from natural language.
Mastra's agent abstraction provides a clean separation between LLM logic and Zilliz Cloud tool infrastructure. Connect 10 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
- Collection Management — List, describe, create, and drop vector collections in your cluster
- Memory Control — Load and release collections to optimize cluster resource usage and search availability
- Vector Search — Execute complex vector similarity searches (ANN) using customizable metrics and parameters
- Metadata Querying — Query entities using boolean expressions and metadata filters to find specific records
- Data Maintenance — Insert new vector/scalar data and delete entities from your collections
The Zilliz Cloud MCP Server exposes 10 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 Zilliz Cloud to Mastra AI via MCP
Follow these steps to integrate the Zilliz Cloud 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 10 tools from Zilliz Cloud via MCP
Why Use Mastra AI with the Zilliz Cloud MCP Server
Mastra AI provides unique advantages when paired with Zilliz Cloud through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure — add Zilliz Cloud 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 Zilliz Cloud 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
Zilliz Cloud + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the Zilliz Cloud MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query Zilliz Cloud, process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed Zilliz Cloud as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query Zilliz Cloud on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using Zilliz Cloud tools alongside other MCP servers
Zilliz Cloud MCP Tools for Mastra AI (10)
These 10 tools become available when you connect Zilliz Cloud to Mastra AI via MCP:
create_collection
Requires a JSON body. Create a new vector collection
delete_entities
Delete entities from a collection
describe_collection
Get details for a specific collection
drop_collection
Drop a collection
insert_entities
Insert data into a collection
list_collections
List all collections in the Zilliz cluster
load_collection
Load a collection into memory
query_entities
Query entities using metadata filtering
release_collection
Release a collection from memory
search_vectors
Requires a JSON search configuration. Perform a vector similarity search
Example Prompts for Zilliz Cloud in Mastra AI
Ready-to-use prompts you can give your Mastra AI agent to start working with Zilliz Cloud immediately.
"List all vector collections in my Zilliz cluster."
"Show the schema and status for collection 'text_docs'."
"Drop the collection named 'old_data_backup'."
Troubleshooting Zilliz Cloud MCP Server with Mastra AI
Common issues when connecting Zilliz Cloud to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpZilliz Cloud + Mastra AI FAQ
Common questions about integrating Zilliz Cloud 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 Zilliz Cloud 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 Zilliz Cloud to Mastra AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.