Integrate Zilliz Cloud with Claude, Cursor, Chatbots & AI Agents MCP Server

Manage vector collections and perform similarity searches via Zilliz Cloud.

GDPR Free for Subscribers

Compatible with every major AI agent and IDE

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

create

Create collection on Zilliz Cloud

Requires a JSON body. Create a new vector collection

delete

Delete entities on Zilliz Cloud

Delete entities from a collection

describe

Describe collection on Zilliz Cloud

Get details for a specific collection

drop

Drop collection on Zilliz Cloud

Drop a collection

insert

Insert entities on Zilliz Cloud

Insert data into a collection

list

List collections on Zilliz Cloud

List all collections in the Zilliz cluster

load

Load collection on Zilliz Cloud

Load a collection into memory

query

Query entities on Zilliz Cloud

Query entities using metadata filtering

release

Release collection on Zilliz Cloud

Release a collection from memory

Search vectors on Zilliz Cloud

Requires a JSON search configuration. Perform a vector similarity search

Security & Code Integrity Audit

Every tool in the Zilliz Cloud MCP Server is continuously audited by the Vinkius Security Engine. We guarantee zero-trust payload isolation, strict data boundaries, and deterministic execution for enterprise-grade AI agents.

A+Score: 100

How Vinkius protects your data

What happens if the underlying API rate limits my agent?

Our edge infrastructure automatically handles backoffs, queueing, and throttling. If an AI agent sends too many erratic requests, Vinkius manages the rate limits gracefully, ensuring your backend doesn't crash.

How does the AI access my passwords and credentials?

It simply doesn't. On Vinkius, your passwords, API keys, and login details are kept in a secure vault. The AI (like ChatGPT or Claude) merely "asks" Vinkius to perform the task. Vinkius opens the door, does the work, and hands the result back to the AI. Your credentials are never seen, read, or learned by the artificial intelligence.

Why do I need to 'load' a collection before searching?

Zilliz requires collections to be loaded into memory to perform high-performance similarity searches. Use the load_collection tool to make your data available for search.

What if the AI ends up reading customer data or confidential information?

We have a built-in digital "bodyguard" called DLP (Data Loss Prevention). If a tool fetches data and the response contains social security numbers, credit cards, or personal customer info, Vinkius magically blocks and erases that information before it is delivered to the AI. The AI works only with what is strictly necessary, and your sensitive data never leaks.

What can AI Agents do with Zilliz Cloud?

The Zilliz Cloud integration provides structured, LLM-friendly schemas for reliable tool execution within your agentic workflows.

Intelligent similarity search Management

The Zilliz Cloud integration exposes LLM-friendly schemas for similarity search. Tools like Cursor can map natural language directly into executable ai frontier commands.

Prompting vector embeddings Workflows

Use Zilliz Cloud to manage vector embeddings via conversational interfaces. The integration centralizes access control for ai frontier operations performed by ChatGPT.