How to Use the Mode (Collaborative Data Platform) MCP in OpenAI Agents SDK

Spin up production-grade OpenAI Agents SDK workflows that directly query your Mode workspace with built-in guardrails.

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Connect Mode (Collaborative Data Platform) MCP to OpenAI Agents SDK

Create your Vinkius account to connect Mode (Collaborative Data Platform) 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 Mode (Collaborative Data Platform) with OpenAI Agents SDK

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Search Mode reports with OpenAI Agents SDK

The `search_reports` tool lets your OpenAI Agents SDK configuration find specific analytical reports by querying the Mode API directly. The agent can search through active workspace queries, match team keywords, and target specific analytical assets without manual intervention. Once found, the agent uses `get_report` to extract specific parameters and metadata from the matched Mode report token. This lets your production agent verify the exact query structure via the MCP server before passing the data to downstream tasks.

Map analytical spaces and member access

The `list_spaces` tool returns all accessible collection spaces isolating datasets across your Mode organization. Your OpenAI Agents SDK system uses this list to understand how your teams group their SQL queries and visual reports. To verify who owns these assets, the agent calls `list_members` to get the list of active users in the Mode workspace. This lets you build compliance guardrails, ensuring agents only share sensitive report data with authorized team members.

Audit database connections and data sources

The `list_data_sources` tool exposes all active database and warehouse connections currently bound to your Mode account. This lets your OpenAI Agents SDK agent verify which physical database a report queries before running any downstream analysis. By combining this with `get_space`, the agent maps out exactly which data warehouses feed specific Mode collection spaces. You get a clear, programmatic view of your data lineage without opening a browser.

Setup guide

Set up Mode (Collaborative Data Platform) 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 Mode (Collaborative Data Platform) tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Mode (Collaborative Data Platform) 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="Mode (Collaborative Data Platform) Agent",
            instructions="You have access to Mode (Collaborative Data Platform) 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 Mode (Collaborative Data Platform) MCP in OpenAI Agents SDK

Install the python package, import the streamable HTTP client, and pass your Vinkius endpoint URL. Set the tool list caching parameter to true to ensure your agents discover the server capabilities instantly without overhead.

Yes, your agent can run the search tool to scan all accessible spaces. It will find queries and reports based on the API permissions tied to your Vinkius connection token.

You can intercept tool calls like report retrieval before execution. This lets you write custom Python validation logic to block unauthorized report reads based on user context.

This MCP server auto-discovers all 7 tools when you initialize the server context. Your agent instantly knows how to call functions like space listing and data source mapping without manual schema configuration.

All API requests go through the Vinkius V8 sandbox, which never stores your report tokens or query parameters. The connection is ephemeral, and credentials are encrypted at rest.

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