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 LlamaIndex 10 tools — connect in under 2 minutes

Name: Airparser
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Airparser as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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 llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Airparser. "
            "You have 10 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Airparser?"
    )
    print(response)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

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.

LlamaIndex agents combine Airparser tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

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 LlamaIndex 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 LlamaIndex via MCP

Follow these steps to integrate the Airparser MCP Server with LlamaIndex.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

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

Why Use LlamaIndex with the Airparser MCP Server

LlamaIndex provides unique advantages when paired with Airparser through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Airparser tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Airparser tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Airparser, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Airparser tools were called, what data was returned, and how it influenced the final answer

Airparser + LlamaIndex Use Cases

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

Hybrid search: combine Airparser real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Airparser to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Airparser for fresh data

Analytical workflows: chain Airparser queries with LlamaIndex's data connectors to build multi-source analytical reports

Airparser MCP Tools for LlamaIndex (10)

These 10 tools become available when you connect Airparser to LlamaIndex 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 LlamaIndex

Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Airparser + LlamaIndex FAQ

Common questions about integrating Airparser MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Airparser tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.