How do I get my SmartLead API key?

Log in to your SmartLead account at **app.smartlead.ai**. Click **Settings** in the left sidebar. Navigate to the **API** section. Your API key is displayed on this page — click **Copy**. Paste it into the configuration field below.

Can I manage hundreds of sending accounts?

Yes. SmartLead is built for scale. Your AI agent can manage mailbox rotation, warm-up status, and daily sending limits across all accounts from a single conversation.

How does mailbox rotation work?

SmartLead automatically distributes outgoing emails across your connected mailboxes, keeping each under safe daily sending limits. Your AI agent monitors this rotation and alerts you if any account approaches its limit.

Is SmartLead good for agencies?

Yes. SmartLead is built specifically for cold email agencies with white-label capabilities, client management, and unlimited mailbox connections — all accessible through your AI agent.

SmartLead MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: SmartLead
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

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

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

Connect SmartLead to your AI agent and manage your cold email infrastructure at scale.

Pydantic AI validates every SmartLead 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

Campaign Management — Create, edit, and monitor campaigns with multi-mailbox rotation.
Lead Management — Upload leads, track statuses, and manage engagement across campaigns.
Email Account Rotation — Monitor sending accounts, warm-up scores, and inbox placement rates.
Analytics — Pull campaign performance metrics including opens, clicks, replies, and conversions.

The SmartLead 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.

How to Connect SmartLead to Pydantic AI via MCP

Follow these steps to integrate the SmartLead 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 8 tools from SmartLead with type-safe schemas

Why Use Pydantic AI with the SmartLead MCP Server

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

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

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

SmartLead + Pydantic AI Use Cases

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

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

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

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

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

SmartLead MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect SmartLead to Pydantic AI via MCP:

add_lead

Add lead

get_campaign

Get campaign

get_campaign_analytics

Get campaign analytics

list_campaigns

List campaigns

list_email_accounts

List email accounts

list_leads

List leads

pause_campaign

Pause campaign

resume_campaign

Resume campaign

Example Prompts for SmartLead in Pydantic AI

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

"What's the status of my 'Enterprise Q2' campaign?"

"Check warm-up progress on my sending accounts."

"Upload 500 new leads to the 'SaaS Founders' campaign."

Troubleshooting SmartLead MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

SmartLead + Pydantic AI FAQ

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