How do I find my Airparser API Key?

Log in to your Airparser account and navigate to **Account Settings** or **API** section. You can generate and copy your unique API key from there. It must be used in the `X-API-Key` header.

Can I get parsing results immediately?

Yes! Use the `parse_document_sync` tool. It waits for Airparser to finish processing (up to 60 seconds) and returns the extracted JSON data directly in the response.

Does this support multi-item tables like line items in an invoice?

Yes, Airparser handles nested structures and tables. Ensure your **Extraction Schema** in the inbox is configured to capture these fields, and they will be returned as structured JSON arrays.

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

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

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

Connect your Airparser account to your AI agent to unlock professional unstructured data extraction and IDP (Intelligent Document Processing). From automatically parsing complex invoices and resumes to auditing extraction schemas and managing automated webhooks, your agent handles your data processing pipeline through natural conversation.

Pydantic AI validates every Airparser 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

Document Parsing — Upload and parse PDFs, emails (EML/HTML), and images synchronously or asynchronously
Inbox Management — List and audit your Airparser inboxes to organize different document types and sources
Schema Orchestration — Retrieve and verify extraction schemas to ensure your structured data matches your database requirements
Automated Workflows — List and create webhooks to automatically push parsed JSON data to your external applications
Real-time Status — Monitor document processing statuses and retrieve historical parsing results directly from chat

The Airparser 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 Airparser to Pydantic AI via MCP

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

Why Use Pydantic AI with the Airparser MCP Server

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

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

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

Airparser + Pydantic AI Use Cases

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

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

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

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

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

Airparser MCP Tools for Pydantic AI (10)

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

create_webhook

Add automated data export

delete_webhook

Remove automated export

get_document_details

Get extracted JSON data

get_inbox_details

Get inbox metadata

get_inbox_schema

Get extraction field definitions

list_documents

List documents in inbox

list_inboxes

List Airparser inboxes

list_webhooks

List inbox webhooks

parse_document_async

Parse document in background

parse_document_sync

Parse document immediately

Example Prompts for Airparser in Pydantic AI

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

"List all inboxes in my Airparser account."

"Show me the extraction schema for inbox ID 'abc-123'."

"Check the status of document ID 'doc_98765'."

Troubleshooting Airparser MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Airparser + Pydantic AI FAQ

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