How to Use the Kissmetrics MCP in OpenAI Agents SDK

Q: Can OpenAI Agents SDK use Kissmetrics to segment users?

Absolutely. You can call querypeoplecount to fetch segments and pass those counts into your agent's system prompt to influence how it talks to specific cohorts.

Connect your OpenAI Agents SDK to your behavior data. Track events and query metrics with verified guardrails in your production pipeline.

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Connect Kissmetrics MCP to OpenAI Agents SDK

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

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Trigger events from your agents

Your agent can now push user behavior directly into your analytics stack. Use `record_event` to log interactions the moment they happen. This keeps your funnel data fresh without manual code changes. Your agent calls the tool, and the data hits your dashboard instantly.

Map identities within OpenAI Agents SDK

Stop losing track of users when they switch devices. Use `alias_identities` to link anonymous IDs to known emails during your agent's execution flow. This ensures your attribution stays clean across the entire user lifecycle. It's the only way to keep your cohort analysis from breaking.

Pull metrics directly into your logic

Stop switching tabs to check your growth numbers. Use `query_metric_data` to feed live performance stats back into your agent's decision-making process. This lets your agent adjust its strategy based on real-time count data. It turns your analytics into a live feedback loop for your automation.

Setup guide

Set up Kissmetrics 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 Kissmetrics tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Kissmetrics 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="Kissmetrics Agent",
            instructions="You have access to Kissmetrics tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Kissmetrics. 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.

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Common questions about Kissmetrics MCP in OpenAI Agents SDK

Install the MCP server via our managed endpoint and add it to your agent constructor. The SDK automatically discovers all seven tools, making them available for immediate use.

Yes, it uses the standard async context manager pattern. This keeps your agent responsive while waiting for the Kissmetrics API to confirm your data writes.

Absolutely. You can call `query_people_count` to fetch segments and pass those counts into your agent's system prompt to influence how it talks to specific cohorts.

Wrap your tool calls in standard Python try-except blocks. If an API request fails, the agent receives the error message directly and can decide whether to retry or log the failure.

Your agent transmits specific user event data directly to your Kissmetrics account. We use ephemeral connections for every request, ensuring no logs persist after the transaction is complete.

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