Can I check my current MRR through the agent?

Yes. Use the `get_mrr` tool to retrieve your current Monthly Recurring Revenue. Your agent will return the latest calculated value directly in the chat.

How do I find a specific customer's subscription history?

First, use `list_customers` with a search term to find the customer's OID. Then, your agent can retrieve their detailed profile and subscription logs to summarize their journey.

Can the agent analyze churn rates for specific periods?

Absolutely. Use the `get_churn_rate` tool and provide a `start_date` and `end_date` (as Unix timestamps) to see the churn metrics for that specific timeframe.

Baremetrics MCP Server for Pydantic AI 12 tools — connect in under 2 minutes

Name: Baremetrics
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 12 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Baremetrics 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 Baremetrics "
            "(12 tools)."
        ),
    )

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

Unlock the pulse of your subscription business with Baremetrics, the leading financial analytics platform for SaaS. By connecting Baremetrics to your AI agent, you transform complex revenue data into a natural conversation. Your agent can instantly retrieve high-level metrics like MRR (Monthly Recurring Revenue), LTV (Lifetime Value), and churn rates, or dive deep into specific customer subscription histories without you ever navigating through dense financial dashboards. Whether you're preparing a board report or auditing customer health, your agent acts as a real-time CFO, ensuring your growth data is always accessible and actionable.

Pydantic AI validates every Baremetrics 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

Financial Auditing — Retrieve instant summaries of core SaaS metrics including MRR, ARR, LTV, and active customer counts via natural language.
Customer Oversight — List and search for specific customers, auditing their internal IDs, profile details, and subscription status.
Subscription Tracking — Access detailed logs of user subscriptions to identify upgrade patterns or potential churn risks.
Source Management — List all available data sources and defined plans to map your entire billing ecosystem.
Custom Timeframes — Query financial metrics for specific date ranges to analyze growth trends and seasonal performance.

The Baremetrics MCP Server exposes 12 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 Baremetrics to Pydantic AI via MCP

Follow these steps to integrate the Baremetrics 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 12 tools from Baremetrics with type-safe schemas

Why Use Pydantic AI with the Baremetrics MCP Server

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

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

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

Baremetrics + Pydantic AI Use Cases

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

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

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

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

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

Baremetrics MCP Tools for Pydantic AI (12)

These 12 tools become available when you connect Baremetrics to Pydantic AI via MCP:

get_account_check

Verify Baremetrics connection

get_active_customers

Convenience tool to get active customer count

get_churn_rate

Convenience tool to get user churn rate

get_customer

Get details for a specific customer

get_ltv

Convenience tool to get Customer Lifetime Value (LTV)

get_metric

Get specific data for a single metric type

get_mrr

Convenience tool to get Monthly Recurring Revenue (MRR)

list_customers

List all customers in Baremetrics

list_metrics

List high-level financial metrics summary

list_plans

List all defined plans

list_sources

List all available data sources

list_subscriptions

List all user subscriptions

Example Prompts for Baremetrics in Pydantic AI

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

"What is my current Monthly Recurring Revenue (MRR)?"

"Show me the top 5 customers by LTV."

"Search for a customer named 'John Smith' and show their active subscriptions."

Troubleshooting Baremetrics MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Baremetrics + Pydantic AI FAQ

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