How do I find my Paperform Access Token?

In your Paperform account, go to **Account Settings** > **API**. There you can create and manage your API access tokens.

Can I see individual form responses?

Yes! Use the `list_submissions` tool to see a list of responses for a specific form, and `get_submission` to retrieve the full data for a particular entry.

Does this support webhook management?

Absolutely. You can use the `list_webhooks` and `create_webhook` tools to monitor and configure integrations for any of your forms.

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

Name: Paperform
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 Paperform 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 Paperform "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Paperform MCP Server

Connect your Paperform account to any AI agent and take full control of your data collection workflows through natural conversation.

Pydantic AI validates every Paperform 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

Form Oversight — List all forms, retrieve detailed configurations, and manage your form library.
Submission Tracking — List and retrieve detailed data for form submissions to analyze responses in real-time.
Webhook Management — List and create webhooks for your forms to integrate with other services effortlessly.
Organizational Visibility — List folders and custom domains to maintain a clear view of your account structure.
Metadata Auditing — List all tags used across your forms to ensure consistent categorization.

The Paperform 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 Paperform to Pydantic AI via MCP

Follow these steps to integrate the Paperform 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 Paperform with type-safe schemas

Why Use Pydantic AI with the Paperform MCP Server

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

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

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

Paperform + Pydantic AI Use Cases

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

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

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

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

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

Paperform MCP Tools for Pydantic AI (10)

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

create_webhook

Create a new webhook for a form

get_account_info

Get authenticated account information

get_form

Get details for a specific form

get_submission

Get details for a specific submission

list_custom_domains

List all custom domains configured

list_folders

List all form folders

list_forms

List all Paperform forms

list_submissions

List submissions for a form

list_tags

List all tags used in the account

list_webhooks

List webhooks for a form

Example Prompts for Paperform in Pydantic AI

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

"List all forms in my Paperform account."

"Show me the last 5 submissions for the 'Event Registration' form."

"List all webhooks configured for form 'form_12345'."

Troubleshooting Paperform MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Paperform + Pydantic AI FAQ

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