How to Use the Qdrant MCP in AutoGen

Q: Can AutoGen use Qdrant to scroll through points?

Yes. The scroll tool is available to all agents. It is useful when your agents need to audit a large number of points to make a collective decision.

Q: Do Qdrant tools work with AutoGen multi-agent setups?

They do. The mcpservertools adapter maps the Qdrant schema directly to your agents, allowing any agent in the group to execute database commands.

Enable debate-driven vector analysis by connecting Qdrant to AutoGen for multi-agent collaboration.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Qdrant MCP to AutoGen

Create your Vinkius account to connect Qdrant to AutoGen — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

GDPR Included with Plan

Setup Qdrant with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Collaborative search with AutoGen

Agents discuss which `search` parameters to use before executing the query. They debate the optimal score threshold to ensure high-quality matches. This improves result accuracy. A second agent can then review the returned payloads and challenge the findings if the similarity scores appear anomalous.

Verify database state across AutoGen agents

Use `list_collections` to allow agents to see what is available. They can negotiate which index holds the relevant data for a specific user request. This prevents redundant operations. The agents agree on the target collection before any search or scroll operation begins.

Manage point deletion through AutoGen

When an agent identifies stale records, it can trigger the `delete` tool. Other agents must approve this action to prevent accidental data loss. This adds a layer of human-in-the-loop validation. The agents reach a consensus before the system performs the irreversible deletion.

Setup guide

Set up Qdrant MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Qdrant tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Qdrant_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Qdrant data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Qdrant_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Qdrant data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Qdrant. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Qdrant now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Qdrant MCP in AutoGen

You pass the MCP tools to your AssistantAgent. During the conversation, agents call `search` as needed, debating the parameters and validating the results before providing a final answer.

Yes. The `scroll` tool is available to all agents. It is useful when your agents need to audit a large number of points to make a collective decision.

They do. The `mcp_server_tools` adapter maps the Qdrant schema directly to your agents, allowing any agent in the group to execute database commands.

You simply define a subset of tools when passing the list to the AssistantAgent constructor. This restricts the agents to only the operations you explicitly allow.

Access is strictly controlled by your endpoint token. The server interacts only with the specific vector payloads the agents need, ensuring your database remains isolated from unauthorized processes.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript