How to Use the HotDocs MCP in OpenAI Agents SDK

Q: How do I connect HotDocs to my OpenAI Agents SDK project?

You initialize the server using the MCPServerStreamableHttp class and pass it into your agent constructor. This setup allows your agent to discover and invoke all 14 tools instantly.

Q: Can OpenAI Agents SDK handle complex HotDocs interview sessions?

Yes, you use createinterviewsession to prepare the data structure. The agent then populates variables via XML through the updateanswers tool.

Q: Does the HotDocs MCP Server support batch updates?

You can call updateanswers repeatedly to add data incrementally. The server processes these updates against the active work item until you trigger the final assembly.

Automate document assembly in your OpenAI Agents SDK production pipeline with direct access to HotDocs templates and work items.

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Connect HotDocs MCP to OpenAI Agents SDK

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

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Full document lifecycle in OpenAI Agents SDK

Your agent manages the entire assembly process by calling `list_template_packages` to find the right form and `create_work_item` to initialize the session. It tracks progress through every step without manual oversight. Once the work item exists, the agent uses `update_answers` to inject data and `complete_assembly` to finalize the output. It handles the heavy lifting so your production system stays focused on logic.

Real-time document retrieval for OpenAI Agents SDK

After the server finalizes an assembly, the agent triggers `list_documents` to identify the correct file ID. This ensures your agent always targets the latest version generated by the system. It then invokes `get_document_content` to pull the binary data for storage or delivery. The process is deterministic and fits perfectly into your agent's existing async workflow.

HotDocs MCP Server status checks

Validation happens automatically when the agent calls `get_unanswered_variables` to verify that all required fields are filled before finalization. This prevents incomplete documents from entering your pipeline. If authentication issues arise, the agent uses `get_auth_token` to verify credentials. It keeps the connection stable and reports failures immediately to your logs.

Setup guide

Set up HotDocs 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 HotDocs tools at runtime.
3

Create your Agent

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

Run the agent

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

You initialize the server using the `MCPServerStreamableHttp` class and pass it into your agent constructor. This setup allows your agent to discover and invoke all 14 tools instantly.

Yes, you use `create_interview_session` to prepare the data structure. The agent then populates variables via XML through the `update_answers` tool.

Your agent pulls document content directly from the HotDocs Advance backend. The server acts as an ephemeral bridge, passing data to your agent without caching it locally.

You can call `update_answers` repeatedly to add data incrementally. The server processes these updates against the active work item until you trigger the final assembly.

The server only touches document metadata and binary content during your active session. It operates in a V8 isolate sandbox, ensuring your sensitive legal data remains isolated from other processes.

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