What credentials do I need to connect HotDocs Advance to this MCP server?

You need four pieces of information: (1) your **Tenancy Moniker** (the subdomain in your HotDocs URL, e.g., 'mycompany' from mycompany.hotdocsadvance.com), (2) the **API Client Display Name** you created in Manage API Credentials, (3) the **Service Principal Name** you added to that client, and (4) the **Service Principal Password** (which is shown only once during creation). All of these are obtained from the HotDocs Advance Auth portal.

Can I assemble documents automatically without going through the interview UI?

Yes! Use the `create_work_item` tool to initialize a work item, then use `update_answers` to inject your data as HotDocs answer XML, and finally call `complete_assembly` to trigger document generation. This fully automated bypasses the interactive interview UI entirely, perfect for batch processing or integrating with external data sources.

How do I find and download documents that have already been assembled?

Use the `list_documents` tool with your workItemId to see all assembled documents and their IDs. Then use `get_document_content` with the workItemId and documentId to retrieve the actual file content. The response includes both the raw content and a direct download URL for easy access to your PDFs or Word documents.

What is a work item and why is it important?

A work item is a unique container in HotDocs Advance that holds interview answers, template associations, and assembled documents for a specific case. Think of it as a 'file folder' for each document automation request. It's identified by a unique ID you assign (like 'contract-john-doe-2024') and persists all data so you can revisit, update, and reassemble documents at any time.

HotDocs MCP Server for Pydantic AI 14 tools — connect in under 2 minutes

Name: HotDocs
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 14 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect HotDocs through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to HotDocs "
            "(14 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in HotDocs?"
    )
    print(result.data)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About HotDocs MCP Server

Connect your HotDocs Advance tenancy to any AI agent and take full control of your document automation workflows through natural conversation.

Pydantic AI validates every HotDocs tool response against typed schemas, catching data inconsistencies at build time. Connect 14 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Template Discovery — List all template packages and their versions available in your HotDocs tenancy
Work Item Management — Create, inspect, and manage work items that hold interview data and assembled documents
Interview Sessions — Initialize interview sessions programmatically for interactive data collection
Automated Document Assembly — Inject answers via XML and trigger document generation without manual UI interaction
Document Retrieval — List and download assembled documents (PDFs, Word docs) directly from the agent
Validation & Auditing — Check unanswered variables, list work items by date range or user, and audit assembly history

The HotDocs MCP Server exposes 14 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect HotDocs to Pydantic AI via MCP

Follow these steps to integrate the HotDocs MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 14 tools from HotDocs with type-safe schemas

Why Use Pydantic AI with the HotDocs MCP Server

Pydantic AI provides unique advantages when paired with HotDocs through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your HotDocs integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your HotDocs connection logic from agent behavior for testable, maintainable code

HotDocs + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the HotDocs MCP Server delivers measurable value.

Type-safe data pipelines: query HotDocs with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple HotDocs tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query HotDocs and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock HotDocs responses and write comprehensive agent tests

HotDocs MCP Tools for Pydantic AI (14)

These 14 tools become available when you connect HotDocs to Pydantic AI via MCP:

complete_assembly

This processes all collected answers and assembles the final documents based on the template configuration. After calling this, the assembled documents become available for download via list_documents and get_document_content. You must have already created a work item, created a version/session, and provided answers (via interview or update_answers). The workItemId and versionId must match an existing work item and its version. Complete document assembly for a work item version

create_interview_session

This endpoint prepares the system to collect answers for the template variables. The response contains interview data needed to render the HotDocs interview UI. Use this before displaying the interview to the user or before assembling documents. The versionId should be unique for each interview session (e.g., v1, v2, or a UUID). Create a new interview session for a work item

create_work_item

A work item is associated with a specific template package and holds answers provided during interviews. You must provide a unique workItemId (alphanumeric identifier you choose) and optionally a templatePackageId. The workItemId becomes the reference for all subsequent operations (interview, assembly, download). IMPORTANT: workItemId must be unique and URL-safe (letters, numbers, hyphens only). Create a new work item in HotDocs Advance

get_auth_token

This is primarily a utility function for debugging authentication issues. The token is used internally by all other tools automatically. If other tools fail with auth errors, verify your credentials are correct. Get a fresh HotDocs API access token

get_document_content

Use this to download the final generated document (PDF, Word, etc.) after assembly is complete. You need the workItemId and the documentId (obtained from list_documents). The response includes the document content and a download URL for direct access. Download/get content of an assembled document

get_template_package

Use the template package ID obtained from list_template_packages. This helps understand the template structure before creating work items. Get details of a specific template package

get_unanswered_variables

This shows which template variables were not provided answers during the interview process. Useful for validating interview completeness before or after document assembly. Requires the workItemId and documentId (from list_documents). The response includes the list of unanswered variables and assembly results. Get unanswered variables from an assembled document

get_work_item

Use this to inspect a work item before or after conducting interviews or assembling documents. The workItemId is the unique identifier you assigned when creating the work item. Get details of a specific work item

list_documents

After completing assembly, this shows all generated documents with their IDs, names, and metadata. Use the document IDs returned here to download individual documents via get_document_content. Each document entry includes filename, creation date, and assembly results information. List all assembled documents for a work item

list_template_packages

Template packages define the structure of documents that can be assembled. Each package contains interview questions and document output configurations. Use this to discover what templates are available for document assembly. The response includes package IDs which are required for creating work items. List all available template packages in HotDocs Advance

list_template_versions

Each template can have multiple versions over time. This shows version history and helps identify which version is currently live/active. Use the package_id from list_template_packages to query versions. List all versions of a template package

list_work_items

You can filter by user ID and/or date range to find specific work items. Leave all parameters empty to list all work items. This is useful for auditing, tracking progress, or finding existing work items to continue working on. Date format should be ISO 8601 (e.g., 2024-01-15 or 2024-01-15T10:30:00). List work items with optional filters

list_work_items_by_date

This is optimized for date-based filtering and auditing. Both fromDate and toDate are required for this tool. Use ISO 8601 date format (e.g., 2024-01-01 or 2024-01-01T00:00:00 for datetime). This is useful for generating reports on document assembly activity over time periods. List work items filtered by a specific date range

update_answers

The answer_xml parameter must contain valid HotDocs answer XML format that matches the template variables. This is useful for automated/batch document assembly where you already have the data. You can call this multiple times to incrementally add answers. Answer XML format example: <AnswerSet><A v="VariableName"><V>Answer Value</V></A></AnswerSet> Update answers for a work item using XML answer format

Example Prompts for HotDocs in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with HotDocs immediately.

"List all available template packages in my HotDocs tenancy."

"Create a new work item 'contract-2024-001' using the employment contract template and assemble a document with these details: employee name is John Smith, position is Software Engineer, start date is March 1st 2024, salary is $95,000."

"Show me all work items created in the last 30 days and check if there are any unanswered variables in the documents."

Troubleshooting HotDocs MCP Server with Pydantic AI

Common issues when connecting HotDocs to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

HotDocs + Pydantic AI FAQ

Common questions about integrating HotDocs MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your HotDocs MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.