How to Use the Hightouch (Reverse ETL) MCP in OpenAI Agents SDK

Q: How do I configure the Hightouch (Reverse ETL) toolset in OpenAI Agents SDK?

Install openai-agents and initialize the MCPServerStreamableHttp client with your Vinkius endpoint. Pass this server instance directly to your agent's constructor to expose the tools instantly.

Q: Does OpenAI Agents SDK support caching for these tools?

Yes, you can set cacheToolsList=True in your parameters. This prevents the agent from making redundant schema discovery requests every time it needs to check your models.

Run production OpenAI Agents SDK setups that audit, verify, and debug Hightouch syncs without manual MCP tool configuration.

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Connect Hightouch (Reverse ETL) MCP to OpenAI Agents SDK

Create your Vinkius account to connect Hightouch (Reverse ETL) 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 Hightouch (Reverse ETL) with OpenAI Agents SDK

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Automate sync triage with OpenAI Agents SDK

Your OpenAI Agents SDK system monitors pipeline health by executing `list_sync_runs` to inspect execution history when errors occur. Instead of digging through log files, the OpenAI model identifies the exact Hightouch step that failed. To diagnose the root cause, the OpenAI Agents SDK calls `get_sync` to pull configuration details. It quickly highlights schema mismatches or credential errors in your Hightouch sync.

Map data lineage via the MCP Server

Your OpenAI Agents SDK system maps operational data flows by querying `list_sources` and `list_destinations` to build a live topology. This gives your team absolute clarity on where Hightouch warehouse records are traveling. By coupling these MCP tools with `list_models`, the OpenAI Agents SDK verifies the SQL logic behind every active Hightouch sync. You avoid sending dirty data through Hightouch to production Salesforce or HubSpot instances.

Safe multi-agent handoffs for operations

Specialized OpenAI Agents SDK instances supervise synchronization health by querying `list_syncs` to detect inactive Hightouch pipelines. A monitoring agent can flag a Hightouch issue and instantly pass the payload to an escalation agent. Built-in guardrails in the OpenAI Agents SDK ensure these agents only read Hightouch configuration metadata. They can't modify your production Hightouch SQL models or delete existing destination configurations.

Setup guide

Set up Hightouch (Reverse ETL) 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 Hightouch (Reverse ETL) tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Hightouch (Reverse ETL) 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="Hightouch (Reverse ETL) Agent",
            instructions="You have access to Hightouch (Reverse ETL) 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 Hightouch (Reverse ETL) MCP in OpenAI Agents SDK

Install `openai-agents` and initialize the `MCPServerStreamableHttp` client with your Vinkius endpoint. Pass this server instance directly to your agent's constructor to expose the tools instantly.

No, this integration only supports read operations. Your agents can query `list_syncs` or check status with `list_sync_runs`, but they cannot write data or trigger new sync jobs.

Yes, you can set `cacheToolsList=True` in your parameters. This prevents the agent from making redundant schema discovery requests every time it needs to check your models.

One agent polls the run history while another analyzes the configuration. The first agent identifies failures, then passes the context to a debugging specialist that calls `get_sync` to isolate the bug.

Only sync metadata, model names, and run statuses are exposed. Your actual warehouse record data never passes through this connection; only structural configuration from tools like `list_destinations` is visible to the model over this MCP connection.

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