ChartMogul MCP Server for Pydantic AIGive Pydantic AI instant access to 12 tools to Create Customer Record, Get Api Status, Get Arr History, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect ChartMogul through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
Ask AI about this App Connector for Pydantic AI
The ChartMogul app connector for Pydantic AI is a standout in the Data Analytics category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 ChartMogul "
"(12 tools)."
),
)
result = await agent.run(
"What tools are available in ChartMogul?"
)
print(result.data)
asyncio.run(main())
* 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 ChartMogul MCP Server
Connect your ChartMogul account to any AI agent and take full control of your SaaS revenue intelligence and subscription monitoring workflows through natural conversation.
Pydantic AI validates every ChartMogul 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
- Revenue Orchestration — Retrieve real-time metrics for Monthly Recurring Revenue (MRR), Annual Run Rate (ARR), and Average Revenue Per Account (ARPA) programmatically
- Churn & Retention Intelligence — Monitor customer churn rates and LTV (Lifetime Value) metrics across custom time intervals to understand your business health in real-time
- Customer Lifecycle Management — List and manage your subscriber base programmatically, including retrieving detailed historical profiles and MRR contributions
- Infrastructure Monitoring — Access information about your connected data sources (Stripe, Braintree, etc.) and subscription plans to ensure high-fidelity billing oversight
- Trend Analysis — Query historical metrics over specific periods (day, week, month, quarter) to identify growth patterns and seasonal shifts directly through your agent
The ChartMogul 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.
All 12 ChartMogul tools available for Pydantic AI
When Pydantic AI connects to ChartMogul through Vinkius, your AI agent gets direct access to every tool listed below — spanning mrr-tracking, saas-analytics, churn-analysis, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Add new customer
Check connection
Analyze ARR
Analyze retention
Monitor user growth
Get customer profile
Check Customer LTV
Analyze MRR
Get key SaaS metrics
List SaaS customers
) connected to ChartMogul. List connected sources
List billing plans
Connect ChartMogul to Pydantic AI via MCP
Follow these steps to wire ChartMogul into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the ChartMogul MCP Server
Pydantic AI provides unique advantages when paired with ChartMogul 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 ChartMogul integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your ChartMogul connection logic from agent behavior for testable, maintainable code
ChartMogul + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the ChartMogul MCP Server delivers measurable value.
Type-safe data pipelines: query ChartMogul with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple ChartMogul tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query ChartMogul and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock ChartMogul responses and write comprehensive agent tests
Example Prompts for ChartMogul in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with ChartMogul immediately.
"Show our MRR and ARR summary for the last 3 months."
"What is our current churn rate compared to last month?"
"Get the MRR contribution for customer 'john.doe@example.com'."
Troubleshooting ChartMogul MCP Server with Pydantic AI
Common issues when connecting ChartMogul to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiChartMogul + Pydantic AI FAQ
Common questions about integrating ChartMogul MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.