How to Use the Mode (Collaborative Data Platform) MCP in AutoGen

Q: How do I register Mode (Collaborative Data Platform) tools in an AutoGen agent team?

You use the mcpservertools helper from the AutoGen extension package. This automatically converts the Mode schemas using this MCP adapter so your AssistantAgent can call tools like listreports during a debate.

Q: Can AutoGen agents collaborate to clean up Mode (Collaborative Data Platform) spaces?

Yes, they can. One agent can call listspaces to find empty collections, while another uses getspace to verify if they should be archived.

Q: How do AutoGen agents handle conflicting data from Mode (Collaborative Data Platform) reports?

The agents use getreport to fetch raw parameters and debate the results. They won't return an answer to the user until they reach a consensus on the data's accuracy.

Deploy AutoGen multi-agent teams to audit, search, and organize your Mode reports through consensus-driven debate.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Mode (Collaborative Data Platform) MCP to AutoGen

Create your Vinkius account to connect Mode (Collaborative Data Platform) to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Mode (Collaborative Data Platform) with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Let AutoGen agents debate your Mode workspace structure

The `list_spaces` tool allows your AutoGen agents to inspect how your analytics workspace is organized. A workspace agent can propose a cleanup plan while a security agent reviews the spaces for compliance. By using `get_space`, the agents can drill down into specific collections to resolve disputes. They negotiate the best way to categorize reports before presenting a final recommendation.

Multi-agent auditing of Mode data sources via MCP Server

This MCP server exposes `list_data_sources` to let your agent teams verify database connections. One agent can pull the list of connections while another cross-references them against active reports. If an agent finds an orphaned database connector, it triggers a debate on whether to deprecate it. This automated negotiation prevents accidental deletion of critical data pipelines.

Coordinate report search and member mapping

Running `search_reports` lets your agents hunt down duplicate analytical queries across the platform. The agents coordinate their search terms to cover different departments and spaces. The team then uses `list_members` and `list_reports` to attribute these duplicates to specific users. They draft a combined summary detailing which reports can be consolidated.

Setup guide

Set up Mode (Collaborative Data Platform) 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 Mode (Collaborative Data Platform) 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="Mode (Collaborative Data Platform)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Mode (Collaborative Data Platform) 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="Mode (Collaborative Data Platform)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Mode (Collaborative Data Platform) 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 Mode. 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 Mode (Collaborative Data Platform) 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 Mode (Collaborative Data Platform) MCP in AutoGen

You use the `mcp_server_tools` helper from the AutoGen extension package. This automatically converts the Mode schemas using this MCP adapter so your AssistantAgent can call tools like `list_reports` during a debate.

Yes, they can. One agent can call `list_spaces` to find empty collections, while another uses `get_space` to verify if they should be archived.

The agents use `get_report` to fetch raw parameters and debate the results. They won't return an answer to the user until they reach a consensus on the data's accuracy.

It supports both stdio and Streamable HTTP transports. You'll typically use HTTP when running your AutoGen agents in a distributed environment.

It routes all database connector listings and member data through a zero-trust Vinkius proxy. Your AutoGen agents only see the filtered outputs they need to resolve their debates.

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