Fidelizador MCP Server for Pydantic AIGive Pydantic AI instant access to 8 tools to Create Contact, Create Mailing List, Delete Contact, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Fidelizador 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 Fidelizador app connector for Pydantic AI is a standout in the Marketing Automation category — giving your AI agent 8 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 Fidelizador "
"(8 tools)."
),
)
result = await agent.run(
"What tools are available in Fidelizador?"
)
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 Fidelizador MCP Server
Connect your Fidelizador account to any AI agent and take full control of your email marketing and automation workflows through natural conversation.
Pydantic AI validates every Fidelizador tool response against typed schemas, catching data inconsistencies at build time. Connect 8 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
- Audience Orchestration — List and manage your email contacts programmatically, including creating, updating, and deleting profiles directly from your agent
- Campaign Management — Monitor your active and past email campaigns and retrieve detailed performance statistics and metadata programmatically
- List Intelligence — Create and manage mailing lists (segmentations) to maintain a structured and high-fidelity organization of your audience
- Relational Integrity — Access complete contact directories and retrieve granular details like phone numbers and custom data points
- System Monitoring — Check campaign statuses and manage subscriber lifecycles directly through your agent for instant marketing reporting
The Fidelizador MCP Server exposes 8 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 8 Fidelizador tools available for Pydantic AI
When Pydantic AI connects to Fidelizador through Vinkius, your AI agent gets direct access to every tool listed below — spanning audience-segmentation, loyalty-programs, personalized-campaigns, 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.
Create a new contact
Create a new mailing list
Delete a contact
Get campaign details
List email campaigns
List contacts in Fidelizador
List mailing lists
Update an existing contact
Connect Fidelizador to Pydantic AI via MCP
Follow these steps to wire Fidelizador 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 Fidelizador MCP Server
Pydantic AI provides unique advantages when paired with Fidelizador 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 Fidelizador integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Fidelizador connection logic from agent behavior for testable, maintainable code
Fidelizador + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Fidelizador MCP Server delivers measurable value.
Type-safe data pipelines: query Fidelizador with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Fidelizador tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Fidelizador and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Fidelizador responses and write comprehensive agent tests
Example Prompts for Fidelizador in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Fidelizador immediately.
"List all my email campaigns in Fidelizador."
"Create a new contact 'John Doe' (john@example.com) in Fidelizador."
"Show me the details for campaign ID '101'."
Troubleshooting Fidelizador MCP Server with Pydantic AI
Common issues when connecting Fidelizador to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiFidelizador + Pydantic AI FAQ
Common questions about integrating Fidelizador 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.