How do I generate an Apperio API token?

Log in to Apperio, go to your user profile section, and look for API settings or tokens. You can generate a new token there which identifies your organization and user permissions.

Can I see line-item details for an invoice?

Yes, the `get_invoice_details` tool provides full details including line items and spend breakdown for a specific invoice.

What legal matters can I access via the API?

The API tokens inherit the permissions of the user who generated them. You will be able to access the same matters and invoices that you can see when logged into the Apperio platform.

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

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

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

The Apperio MCP Server provides a powerful natural language interface to your legal spend management platform. Connect your Apperio account to your AI agent to gain real-time visibility into your legal matters, track e-billing status, and streamline your invoice approval workflows.

Pydantic AI validates every Apperio 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.

Key Capabilities

Matter Tracking — List all legal matters and get detailed header information for any specific case.
E-billing Management — Access your invoices, view detailed line items, and track total spend across firms.
Workflow Automation — Approve or reject invoices directly from your chat interface and view current approval paths.
Matter Categorization — Manage and apply tags to your matters for better organization and reporting.
Real-time Insights — Get instant answers about your legal cases and financial status without navigating complex dashboards.

The Apperio 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 Apperio to Pydantic AI via MCP

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

Why Use Pydantic AI with the Apperio MCP Server

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

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

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

Apperio + Pydantic AI Use Cases

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

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

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

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

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

Apperio MCP Tools for Pydantic AI (10)

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

approve_invoice

Approve a legal invoice

get_account_check

Verify Apperio account connection

get_invoice_approval_workflow

Get the approval workflow path for an invoice

get_invoice_details

Get full details for a specific invoice

get_matter_header

Get high-level information about a specific matter

list_invoices

List all e-billing invoices available in Apperio

list_matter_tags

List all available matter tags

list_matters

List all legal matters tracked in Apperio

reject_invoice

Should usually be followed by a reason in the platform. Reject a legal invoice

tag_matter

Apply tags to a specific matter

Example Prompts for Apperio in Pydantic AI

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

"List all active legal matters in Apperio."

"Show me the last 5 invoices pending approval."

"Approve invoice with ID 'inv_12345'."

Troubleshooting Apperio MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Apperio + Pydantic AI FAQ

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