How do I find my Cluster Endpoint?

You can find your Cluster Endpoint in the Zilliz Cloud Console under the 'Cluster Details' page. It typically looks like `https://in01-xxxxxxxxxxxx.vectordb.zillizcloud.com`.

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.

Can I filter my vector search using metadata?

Yes, Zilliz supports hybrid search. You can use the `query_entities` tool for metadata-only filtering or include filtering expressions in your `search_vectors` JSON configuration.

Zilliz Cloud MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes

Name: Zilliz Cloud
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 10 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Zilliz Cloud through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Zilliz Cloud Assistant",
            instructions=(
                "You help users interact with Zilliz Cloud. "
                "You have access to 10 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Zilliz Cloud"
        )
        print(result.final_output)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

The OpenAI Agents SDK auto-discovers all 10 tools from Zilliz Cloud through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Zilliz Cloud, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.

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 OpenAI Agents SDK 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 OpenAI Agents SDK via MCP

Follow these steps to integrate the Zilliz Cloud MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 10 tools from Zilliz Cloud

Why Use OpenAI Agents SDK with the Zilliz Cloud MCP Server

OpenAI Agents SDK provides unique advantages when paired with Zilliz Cloud through the Model Context Protocol.

Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Zilliz Cloud + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Zilliz Cloud MCP Server delivers measurable value.

Automated workflows: build agents that query Zilliz Cloud, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents — one queries Zilliz Cloud, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Zilliz Cloud tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Zilliz Cloud to resolve tickets, look up records, and update statuses without human intervention

Zilliz Cloud MCP Tools for OpenAI Agents SDK (10)

These 10 tools become available when you connect Zilliz Cloud to OpenAI Agents SDK 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 OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK 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 OpenAI Agents SDK

Common issues when connecting Zilliz Cloud to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Zilliz Cloud + OpenAI Agents SDK FAQ

Common questions about integrating Zilliz Cloud MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.