Stigg MCP Server for Pydantic AIGive Pydantic AI instant access to 12 tools to Gql Get Customer, Gql Get Entitlements State, Gql Provision Customer, and more

Name: Stigg
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 Stigg through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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The Stigg MCP Server for Pydantic AI is a standout in the Developer Tools 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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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 Stigg "
            "(12 tools)."
        ),
    )

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

Connect your Stigg account to any AI agent to take full control of your pricing and packaging workflows. Manage the entire customer lifecycle from provisioning to usage reporting through natural conversation.

Pydantic AI validates every Stigg 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 Lifecycle — Create, update, and retrieve customer profiles using REST or GraphQL tools.
Subscription Management — Provision new subscriptions, fetch active plan details, or cancel them when needed.
Usage Reporting — Report metered feature usage in real-time to ensure accurate billing and entitlement enforcement.
Hybrid API Access — Choose between REST and GraphQL actions for flexible integration with your billing data.

The Stigg 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 Stigg tools available for Pydantic AI

When Pydantic AI connects to Stigg through Vinkius, your AI agent gets direct access to every tool listed below — spanning billing, subscriptions, saas-pricing, 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.

gql

Gql get customer on Stigg

Get customer details via GraphQL

gql

Gql get entitlements state on Stigg

Get entitlements state via GraphQL

gql

Gql provision customer on Stigg

Provision a customer and optional subscription via GraphQL

gql

Gql provision subscription on Stigg

Provision a subscription via GraphQL

gql

Gql report usage on Stigg

Report usage via GraphQL

rest

Rest cancel subscription on Stigg

Cancel a subscription via REST API

rest

Rest create customer on Stigg

Create a new customer via REST API

rest

Rest create subscription on Stigg

Create a subscription via REST API

rest

Rest get customer on Stigg

Retrieve a customer via REST API

rest

Rest get subscription on Stigg

Retrieve a subscription via REST API

rest

Rest report usage on Stigg

Report usage for metered features via REST API

rest

Rest update customer on Stigg

Update a customer via REST API

Connect Stigg to Pydantic AI via MCP

Follow these steps to wire Stigg 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 Stigg with type-safe schemas

Why Use Pydantic AI with the Stigg MCP Server

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

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

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

Stigg + Pydantic AI Use Cases

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

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

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

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

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

Example Prompts for Stigg in Pydantic AI

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

"Create a customer with ID 'cust_123', name 'Alice', and email 'alice@example.com' using REST."

"Report 50 units of usage for feature 'api-calls' for customer 'cust_123'."

"Get the details for customer 'cust_123' using GraphQL."

Troubleshooting Stigg MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Stigg + Pydantic AI FAQ

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