How to Use the Zilliz Cloud MCP in OpenAI Agents SDK

Q: How do I query data from Zilliz Cloud using OpenAI Agents SDK?

You call queryentities with specific metadata filters. The agent handles the structure, making sure your search runs efficiently against the vectors in Zilliz Cloud.

Q: Can I manage multiple collections using Zilliz Cloud and OpenAI Agents SDK?

Yes. You first run listcollections to see what exists. Then you can use tools like createcollection or dropcollection on any collection name found in the list.

Q: If I run a complex search query, which tools are involved when using Zilliz Cloud and OpenAI Agents SDK?

The primary tool is searchvectors. But depending on the filters required, it might also call queryentities to narrow down results before running the final vector comparison.

Execute complex vector searches and manage collections reliably with your OpenAI Agents SDK.

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Connect Zilliz Cloud MCP to OpenAI Agents SDK

Create your Vinkius account to connect Zilliz Cloud to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Zilliz Cloud with OpenAI Agents SDK

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Vector Search & Retrieval

You use the `search_vectors` tool to perform similarity searches. It takes a JSON search configuration and returns relevant entities based on vector proximity. This lets your AI client connect directly to Zilliz Cloud, retrieving specific data chunks by running metadata filters alongside the vector match.

Managing Collections

Start by calling `list_collections` to see everything available in the cluster. You then use `describe_collection` if you need details on a specific group. Need to make changes? Use `create_collection` with a JSON body, or wipe it clean using `drop_collection`. The process is straightforward.

Data Ingestion

Don't just search—add data. Call `insert_entities` to load new records into your target collection. You can also use `load_collection` if you need the entire set of entities in memory for faster processing later on.

Setup guide

Set up Zilliz Cloud MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Zilliz Cloud tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Zilliz Cloud tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Zilliz Cloud tools and returns structured results. Copy the full example on the right to get started.

agent.py

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

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Zilliz Cloud Agent",
            instructions="You have access to Zilliz Cloud tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Zilliz Cloud MCP in OpenAI Agents SDK

You call `query_entities` with specific metadata filters. The agent handles the structure, making sure your search runs efficiently against the vectors in Zilliz Cloud.

This server touches vector and entity data. When you use the OpenAI Agents SDK, your AI client runs within secure guardrails, ensuring that all interactions with Zilliz Cloud remain contained.

Yes. You first run `list_collections` to see what exists. Then you can use tools like `create_collection` or `drop_collection` on any collection name found in the list.

It does. If you need to process a large, fixed dataset, use `load_collection`. This moves the entire collection into memory for your agent client to work with.

The primary tool is `search_vectors`. But depending on the filters required, it might also call `query_entities` to narrow down results before running the final vector comparison.

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