How to Use the Docparser MCP in OpenAI Agents SDK

Q: Can I use Docparser to track failed extractions in OpenAI Agents SDK?

You certainly can. By polling listfaileddocumentextractions, your agent can automatically alert you or attempt a retry. It keeps your pipeline clean of stale, unparsed data.

Automate data extraction directly within your OpenAI Agents SDK workflow to keep your production pipelines moving without manual intervention.

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Connect Docparser MCP to OpenAI Agents SDK

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

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Full Parser Visibility for OpenAI Agents SDK

Stop guessing what your document parsers are doing. Use `list_document_parsers` to pull your entire configuration into the agent context immediately. Once you have the list, `get_parser_details` lets the agent inspect specific settings to ensure the target parser is ready for incoming files.

Automated Extraction Handling

Your agent can grab data from processed files by calling `get_document_extraction_results` the second they hit the system. This removes the wait time between file upload and data availability. If something goes wrong, `list_failed_document_extractions` acts as your audit trail. The agent flags these errors before they impact your downstream databases.

Real-time Parser Health Monitoring

Keep your document pipeline running smooth by calling `quick_parser_health_audit` periodically. It gives you a snapshot of success rates without manual dashboard checks. When you need to find a specific file, `search_parsed_documents` lets the agent locate documents by filename in seconds.

Setup guide

Set up Docparser 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 Docparser tools at runtime.
3

Create your Agent

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

Run the agent

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

You instantiate an MCPServerStreamableHttp object with your endpoint and pass it to your agent constructor. The agent auto-discovers every tool, allowing you to call them as native functions.

Yes. Since your agent treats these tools as standard functions, you can wrap them in your existing validation logic. This ensures that any data returned by the server meets your schema requirements before the agent proceeds.

You certainly can. By polling `list_failed_document_extractions`, your agent can automatically alert you or attempt a retry. It keeps your pipeline clean of stale, unparsed data.

Vinkius manages the transport layer using ephemeral, zero-trust principles. Your API token is the only thing required to establish the connection, keeping your credentials off your local disk.

This server touches raw document metadata and extracted text fields from your invoices, forms, or contracts. We handle this information through encrypted endpoints that discard session data immediately after your agent finishes its task.

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