How to Use the DeckMatch MCP in OpenAI Agents SDK

Q: What happens if the API connection drops during an OpenAI Agents SDK run?

Use getapistatus to check connectivity before starting a task. If the server is unreachable, the agent will catch the error instead of crashing.

Analyze pitch decks and manage investor pipelines directly within your OpenAI Agents SDK agent system.

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Connect DeckMatch MCP to OpenAI Agents SDK

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

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Automate deck triage in OpenAI Agents SDK

Use `submit_pitch_deck` to push incoming files directly into the analysis pipeline. Your agents will handle the heavy lifting without manual intervention. Once processed, trigger `get_deck_analysis` to pull the triage results. It keeps your agent flow moving while it sorts the signal from the noise.

Build audit trails for OpenAI Agents SDK

Call `get_submission_audit` to track every action taken on a specific file. This maintains a clear history of how your agent engaged with the data. Check `get_submission_details` to verify the current status of any record. It ensures your agent logic stays synced with the actual submission state.

Scale deal flow with this MCP Server

Run `search_startups_semantically` to identify similar companies based on your existing portfolio. Your agents can now find matches without static keyword searches. Execute `generate_investment_memo` to turn raw findings into structured notes. This MCP server handles the heavy lifting so your agent can focus on the decision.

Setup guide

Set up DeckMatch 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 DeckMatch tools at runtime.
3

Create your Agent

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

Run the agent

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

You instantiate an MCPServerStreamableHttp object with your endpoint and add it to the mcp_servers list in your Agent constructor. The SDK discovers the 12 tools automatically.

Yes, it treats your pitch deck files and investment memos as private data. Vinkius manages the transport security through isolated ephemeral sessions.

You can limit the toolset by passing only the methods your agent requires. This keeps the model's context window clean and focused on specific tasks.

Use `get_api_status` to check connectivity before starting a task. If the server is unreachable, the agent will catch the error instead of crashing.

It encrypts all submission records at rest and in transit. Your agent only accesses the specific data points requested through the tools.

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OpenAI Agents SDK sdk-python