Lago MCP Server for Pydantic AIGive Pydantic AI instant access to 12 tools to Apply Coupon, Batch Events, Create Billable Metric, and more

Name: Lago
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Lago through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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The Lago MCP Server for Pydantic AI is a standout in the Money Moves category — giving your AI agent 12 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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+ other MCP clients

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 Lago "
            "(12 tools)."
        ),
    )

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

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 Lago MCP Server

Connect Lago to your AI agent to automate your metering and billing infrastructure. Lago is the open-source alternative to Stripe Billing, designed for complex usage-based pricing models.

Pydantic AI validates every Lago tool response against typed schemas, catching data inconsistencies at build time. Connect 12 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

Customer Management — Create and update customer profiles with upsert_customer and retrieve details with get_customer.
Subscription Lifecycle — Assign plans to customers using create_subscription and monitor them with get_subscription.
Billing Infrastructure — Define billing plans with create_plan and set up create_billable_metric to track consumption.
Usage Tracking — Send real-time usage data with send_event or batch_events to trigger accurate billing.
Financial Operations — Manage wallets, apply coupons, and list invoices to keep your revenue operations running smoothly.

The Lago MCP Server exposes 12 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 12 Lago tools available for Pydantic AI

When Pydantic AI connects to Lago through Vinkius, your AI agent gets direct access to every tool listed below — spanning usage-based-billing, metering, saas-metrics, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

apply

Apply coupon on Lago

Apply a coupon to a customer

batch

Batch events on Lago

Send a batch of usage events

create

Create billable metric on Lago

Create a billable metric

create

Create coupon on Lago

Create a coupon

create

Create plan on Lago

Create a new billing plan

create

Create subscription on Lago

Assign a plan to a customer (create subscription)

create

Create wallet on Lago

Create a wallet for prepaid credits

get

Get customer on Lago

Retrieve a customer by external ID

get

Get subscription on Lago

Retrieve a subscription by external ID

list

List invoices on Lago

List all invoices

send

Send event on Lago

Send a usage event

upsert

Upsert customer on Lago

Requires an external_id. Create or update a customer in Lago

Connect Lago to Pydantic AI via MCP

Follow these steps to wire Lago into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 12 tools from Lago with type-safe schemas

Why Use Pydantic AI with the Lago MCP Server

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

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

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

Lago + Pydantic AI Use Cases

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

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

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

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

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

Example Prompts for Lago in Pydantic AI

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

"Create a new customer in Lago with external ID 'user_123' and email 'dev@example.com'."

"Show me the subscription details for ID 'sub_98765'."

"List all invoices for my Lago account."

Troubleshooting Lago MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Lago + Pydantic AI FAQ

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

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