How to Use the AI Token Counter MCP in OpenAI Agents SDK

Stop guessing context limits. The AI Token Counter MCP gives your OpenAI Agents SDK production systems precise token-level control.

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Connect AI Token Counter MCP to OpenAI Agents SDK

Create your Vinkius account to connect AI Token Counter 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 AI Token Counter with OpenAI Agents SDK

Ask AI about this MCP

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Claude

Perplexity

Pre-flight token validation

Your agent checks input size before calling the API. It uses `count_tokens` to calculate exact usage, preventing runtime errors caused by context overflows. This validation layer ensures your agent stays within the specific limits of your model. It saves you from costly retries and failed task execution.

Deterministic memory management

You define exact thresholds for your agent to trigger summarization or data chunking. The `count_tokens` tool provides the hard data needed to automate these decisions. This approach removes the guesswork from managing long-running conversations. Your agent now knows exactly when its memory buffer is nearing capacity.

Production-grade safety guardrails

Integrate token counting directly into your agent setup using the native MCP interface. It runs as a local validation step within your existing agent workflow. This setup keeps your system reliable by catching issues before they hit the network. You get predictable behavior in every deployment.

Setup guide

Set up AI Token Counter 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 AI Token Counter tools at runtime.
3

Create your Agent

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

Run the agent

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

asyncio.run(main())

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