How to Use the HotDocs MCP in Pydantic AI

Q: How do I use HotDocs with Pydantic AI toolsets?

You define an MCPToolset pointing to the server URL and add it to your Agent definition. This gives you full type-safe access to all document assembly tools.

Q: How do I inspect template details in Pydantic AI?

You call gettemplatepackage with the package ID. The agent receives a structured object that you can immediately validate against your Pydantic models.

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Connect HotDocs MCP to Pydantic AI

Create your Vinkius account to connect HotDocs to Pydantic AI 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 Pydantic AI

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Type-safe assembly in Pydantic AI

Every response from the server is validated against your models, ensuring that fields returned by `get_work_item` match your expectations. You catch data mismatches before they reach your business logic. This strict validation prevents silent errors when you interact with `list_template_packages`. Your agent only proceeds if the data structure is perfect.

Validated document generation for Pydantic AI

Your agent uses `create_work_item` to start a session and `update_answers` to push data. Because you use Pydantic AI, any malformed XML in your answer set triggers an immediate validation error. This safety layer ensures that `complete_assembly` always receives the correct input. You avoid the runtime crashes common in less structured environments.

Efficient document retrieval in Pydantic AI

The agent identifies the correct file using `list_documents` and confirms the result with the server. It then fetches the content via `get_document_content`. Since the server is type-checked, your agent correctly maps the download URL and metadata. You get a clean, reliable path from template to final document.

Setup guide

Set up HotDocs MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "hotdocs-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to HotDocs tools.",
)

result = await agent.run("List recent HotDocs transactions")
print(result.output)

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Common questions about HotDocs MCP in Pydantic AI

You define an `MCPToolset` pointing to the server URL and add it to your `Agent` definition. This gives you full type-safe access to all document assembly tools.

Yes, every tool call is validated against the schema. If the server returns unexpected data, Pydantic AI raises a validation error immediately.

Absolutely. Since Pydantic AI is model-agnostic, you can swap between models while keeping the same tool definitions.

You call `get_template_package` with the package ID. The agent receives a structured object that you can immediately validate against your Pydantic models.

The server uses a zero-trust architecture. Your document answers and generated files exist only within an ephemeral sandbox that clears once your task completes.

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