Where do I find my NeverBounce API Key?

Log in to your NeverBounce dashboard and navigate to the API section to create or copy your 'Secret Key'.

What do the different result statuses mean?

'Valid' means the email is safe to send. 'Invalid' will bounce. 'Disposable' are temporary addresses, and 'Catchall' means the domain accepts all mail, making deliverability uncertain.

How do I start a bulk verification job?

First, use `create_job_from_url` or `create_job_from_input`. Then, call `parse_job` followed by `start_job` to begin the verification process.

NeverBounce MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: NeverBounce
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

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

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

Connect your NeverBounce account to your AI agent and ensure your email lists are clean and deliverable through natural conversation.

Pydantic AI validates every NeverBounce tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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 — Check a single email address instantly to get its status (valid, invalid, disposable, etc.).
Bulk Job Management — Create, parse, and start bulk verification jobs from URLs or raw input arrays.
Progress Tracking — Monitor the status and progress of your active bulk jobs in real-time.
Result Retrieval — Fetch the verification results for all emails in a completed job for download or analysis.
Account Oversight — Check your remaining credit balance and list all recent jobs in your history.
Deep Inspection — Fetch detailed metadata and flags for specific email checks or job IDs.

The NeverBounce MCP Server exposes 10 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 NeverBounce to Pydantic AI via MCP

Follow these steps to integrate the NeverBounce 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 10 tools from NeverBounce with type-safe schemas

Why Use Pydantic AI with the NeverBounce MCP Server

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

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

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

NeverBounce + Pydantic AI Use Cases

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

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

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

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

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

NeverBounce MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect NeverBounce to Pydantic AI via MCP:

check_email

Verify a single email address

create_job_from_input

Create a bulk job from raw input

create_job_from_url

Create a bulk job from a remote CSV URL

delete_job

Delete a bulk job

get_account_info

Get account credits and info

get_job_results

Get results of a completed bulk job

get_job_status

Check status of a bulk job

list_jobs

List bulk verification jobs

parse_job

Parse a bulk job

start_job

Start a bulk job

Example Prompts for NeverBounce in Pydantic AI

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

"Verify if the email 'test@example.com' is valid."

"List all my recent verification jobs."

"Check the status of job ID 123456."

Troubleshooting NeverBounce MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

NeverBounce + Pydantic AI FAQ

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