How to Use the BatchDialer MCP in OpenAI Agents SDK

Q: Can I run multiple BatchDialer campaigns simultaneously using OpenAI Agents SDK?

Absolutely, just let your agent query listcampaigns to identify active dialer pools. The agent can then route leads to different campaigns based on your custom Python logic.

Q: How does the agent handle failed calls in BatchDialer?

The agent queries getcalldetails to read the exact termination reason from the dialer. It then logs the outcome using listdispositions to determine if it should retry the number.

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Connect BatchDialer MCP to OpenAI Agents SDK

Create your Vinkius account to connect BatchDialer 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 BatchDialer with OpenAI Agents SDK

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Automate Campaign Management with OpenAI Agents SDK

The `list_campaigns` tool lets your agent pull active dialing lists directly into your OpenAI execution graph. This is the first step to checking what outreach you have running before you drop new leads into the queue. Once the agent finds the right target, it calls `get_campaign` to inspect daily limits and pacing. This prevents your script from pushing contacts into stopped or over-budget lists.

Add Leads and Sync Contact Profiles

The `add_lead` tool inserts new prospects into your active dialer lists during live agent runs. Our MCP server handles the underlying API connection so your agent can focus on formatting. To keep your database clean, the agent uses `get_lead` to check if a contact already exists. This simple check stops duplicate records from messing up your sales pipeline.

Audit Outbound Call History and Dispositions

The `list_call_logs` tool pulls real-time call records so your agent can track performance and connect rates. You get exact timestamps and durations without manual exports. Your agent reads these logs alongside `list_dispositions` to categorize outcomes. This data feeds back into your OpenAI dashboard to trace how your MCP tools are performing.

Setup guide

Set up BatchDialer 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 BatchDialer tools at runtime.
3

Create your Agent

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

Run the agent

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

Use pip to install openai-agents, then pass our Vinkius endpoint URL to MCPServerStreamableHttpParams. Register this server in your mcp_servers list to let your agent discover all ten tools instantly.

Yes. Set cacheToolsList to true in your agent configuration to avoid fetching the tool definitions on every single run. This drops latency significantly when your agent is making rapid decisions.

Absolutely, just let your agent query `list_campaigns` to identify active dialer pools. The agent can then route leads to different campaigns based on your custom Python logic.

The agent queries `get_call_details` to read the exact termination reason from the dialer. It then logs the outcome using `list_dispositions` to determine if it should retry the number.

Vinkius isolates this BatchDialer MCP Server inside a zero-trust V8 sandbox, meaning your call logs and lead lists never touch external storage. Your API keys stay encrypted, and the connection closes immediately after the agent finishes its run.

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