How to Use the Deterministic Text Summarizer & Extractor MCP in OpenAI Agents SDK

Q: How do I connect the Deterministic Text Summarizer & Extractor to the OpenAI Agents SDK?

You install the openai-agents package via pip. Then you initialize MCPServerStreamableHttp with your Vinkius endpoint. Pass that directly into your agent's mcpservers list and it auto-discovers the tools.

Give your OpenAI Agents SDK pure mathematical text extraction. Stop relying on LLMs for basic term frequency.

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Connect Deterministic Text Summarizer & Extractor MCP to OpenAI Agents SDK

Create your Vinkius account to connect Deterministic Text Summarizer & Extractor 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 Deterministic Text Summarizer & Extractor with OpenAI Agents SDK

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Deterministic keyword math for your agent

The Deterministic Text Summarizer & Extractor gives your agent exactly three tools for pure math-based text analysis. You don't always need a billion parameters to find the main idea. Your agent calls `extract_top_keywords` and gets the exact term frequency count, ignoring stop words entirely. LLMs hallucinate summaries. Math does not. When you wire this into your OpenAI Agents SDK setup, your agent runs deterministic extraction before passing context to another specialist agent. You get predictable, repeatable data pipelines.

Build extractive summaries via MCP Server

The `extractive_summary` tool ranks sentences purely by their mathematical importance using term frequency. Your agent feeds it a massive text block. It returns the exact sentences that matter most, stripped of any generative variance. This keeps your production system grounded. You can set up guardrails in your OpenAI setup to ensure the agent only acts on these extracted sentences. It cuts down on token costs and keeps the focus entirely on the source material.

Bigram extraction for strict topic modeling

The `extract_top_bigrams` tool pulls the most frequent two-word phrases straight from your raw text. This is basic, undeniable frequency counting. Your agent grabs these pairs to tag documents or build search indexes. You track everything through the OpenAI dashboard. Because the MCP connection handles the extraction locally, you aren't waiting on a slow external API to parse bigrams. The agent gets the data instantly and moves on to the next step in the pipeline.

Setup guide

Set up Deterministic Text Summarizer & Extractor 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 Deterministic Text Summarizer & Extractor tools at runtime.
3

Create your Agent

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

Run the agent

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

You install the `openai-agents` package via pip. Then you initialize `MCPServerStreamableHttp` with your Vinkius endpoint. Pass that directly into your agent's `mcp_servers` list and it auto-discovers the tools.

Yes. You can loop through documents and call the tools repeatedly. Set `cacheToolsList=True` in your setup so the agent does not waste time re-fetching the tool definitions.

Prompts are unpredictable. If you need exact term frequencies, you need a deterministic script. This server guarantees the math never changes.

The server takes raw string inputs. Your agent needs to extract text from PDFs or HTML first, then pass the clean strings to the extraction tools.

The MCP server processes raw text strings inside a V8 Isolate Sandbox. The environment is completely ephemeral. Once the extraction finishes, the memory wipes clean and zero records remain.

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