Listclean MCP Server for Pydantic AI 5 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Listclean through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Listclean "
"(5 tools)."
),
)
result = await agent.run(
"What tools are available in Listclean?"
)
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 Listclean MCP Server
Connect your Listclean account to any AI agent to automate your email hygiene and deliverability workflows. This MCP server enables your agent to verify single email addresses instantly, process batch validations, and monitor your verification credits directly from natural language interfaces.
Pydantic AI validates every Listclean tool response against typed schemas, catching data inconsistencies at build time. Connect 5 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
- Real-time Verification — Instantly check if an email address is clean, dirty, or risky before sending
- Batch Processing — Validate large lists of email addresses (up to 3,000 per request) efficiently
- History Oversight — Retrieve logs of previously performed single verifications to track your activity
- Credit Management — Monitor your remaining verification credits to ensure uninterrupted service
- Data Quality Audit — Identify catch-all, disposable, and role-based emails to maintain a high-quality contact list
The Listclean MCP Server exposes 5 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 Listclean to Pydantic AI via MCP
Follow these steps to integrate the Listclean 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 5 tools from Listclean with type-safe schemas
Why Use Pydantic AI with the Listclean MCP Server
Pydantic AI provides unique advantages when paired with Listclean 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 Listclean integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Listclean connection logic from agent behavior for testable, maintainable code
Listclean + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Listclean MCP Server delivers measurable value.
Type-safe data pipelines: query Listclean with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Listclean tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Listclean and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Listclean responses and write comprehensive agent tests
Listclean MCP Tools for Pydantic AI (5)
These 5 tools become available when you connect Listclean to Pydantic AI via MCP:
check_account_credits
Check remaining verification credits
get_account_profile
Get account profile details
get_verification_logs
Retrieve logs of previously verified single emails
verify_batch_emails
Maximum recommended size is 3,000 per request. Verify multiple email addresses in one batch
verify_single_email
Requires a single email string. Verify a single email address in real-time
Example Prompts for Listclean in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Listclean immediately.
"Verify the email address 'test@example.com' in Listclean."
"Show my recent email verification logs."
"How many verification credits do I have left?"
Troubleshooting Listclean MCP Server with Pydantic AI
Common issues when connecting Listclean to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiListclean + Pydantic AI FAQ
Common questions about integrating Listclean 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.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect Listclean with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Listclean to Pydantic AI
Get your token, paste the configuration, and start using 5 tools in under 2 minutes. No API key management needed.