How do I get a Documint API Key?

Log in to your Documint account, navigate to the API section in your account settings, and you can generate or retrieve your unique API Key from there.

Can the agent show me the variables for a template?

Yes, you can use the get_template_variable_audit tool to retrieve exactly which data keys are needed to populate a specific template.

What format are the documents generated in?

Documint specializes in generating high-quality PDF files from your dynamic HTML or designed templates.

Documint MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Documint
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Documint 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 Documint "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Documint?"
    )
    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 Documint MCP Server

Integrate Documint, the versatile document generation and automation platform, directly into your AI workflow. Manage your dynamic document templates, generate professional PDF files from JSON data, and track your generation history using natural language.

Pydantic AI validates every Documint tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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 Oversight — List and retrieve detailed configuration and variable schemas for all your document templates.
Document Generation — Trigger the Documint engine to create new files instantly using provided data variables.
Generation Tracking — Monitor the status of your document generations and access secure download URLs.
Variable Intelligence — Identify exactly which data keys are required to populate specific templates accurately.

The Documint MCP Server exposes 10 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 Documint to Pydantic AI via MCP

Follow these steps to integrate the Documint 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 10 tools from Documint with type-safe schemas

Why Use Pydantic AI with the Documint MCP Server

Pydantic AI provides unique advantages when paired with Documint 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 Documint integration code

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

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

Documint + Pydantic AI Use Cases

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

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

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

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

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

Documint MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Documint to Pydantic AI via MCP:

create_new_generation

Generate a new document using a specific template and data object

get_documint_account_metadata

Retrieve metadata and usage limits for your Documint account

get_generation_details

Get the current status and download URL for a specific generated document

get_template_configuration

Get detailed information and field schema for a specific template

get_template_variable_audit

Identify exactly which variables are required to populate a template

list_documint_generations

List all documents that have been generated in Documint

list_documint_templates

List all available document templates in your Documint account

list_failed_doc_generations

Identify document generations that failed due to errors (mock logic)

list_latest_doc_generations

Identify the most recently generated documents

search_documint_templates

Search for a document template using a name keyword

Example Prompts for Documint in Pydantic AI

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

"List all available Documint templates."

"Generate a new 'Event Ticket' with data: {'guest_name': 'Jane Smith', 'seat': 'A12'}."

"Show me the status of the last 5 generations."

Troubleshooting Documint MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Documint + Pydantic AI FAQ

Common questions about integrating Documint 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 Documint MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.