How to Use the AeroLeads MCP in Pydantic AI

Q: How do I initialize the AeroLeads MCP Server with Pydantic AI?

Install pydantic-ai-slimmcp. Pass your Vinkius endpoint to MCPToolset using the unified HTTP approach. Attach that toolset directly to your Agent instance.

Q: How do I audit the team members on my account?

Write a quick script that calls listteammembers. The agent fetches the user array and validates it against your expected team roster.

Type-safe prospecting with the AeroLeads MCP Server and Pydantic AI. Validate every email, phone number, and LinkedIn profile at runtime.

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Connect AeroLeads MCP to Pydantic AI

Create your Vinkius account to connect AeroLeads to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup AeroLeads with Pydantic AI

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Perplexity

Strict schema validation for the AeroLeads MCP Server

Scraping contact data usually results in messy, unpredictable JSON. Pydantic AI fixes this by enforcing strict models on every response. When your agent calls `search_domain_leads`, it expects specific fields. If the API returns a malformed email address, the framework fails loudly instead of passing garbage data downstream. You define exactly what a valid prospect looks like. The agent uses `find_email_by_name` to hunt down targets. If the returned payload matches your Pydantic model, it proceeds. If not, it catches the validation error and tries a different search strategy.

Type-safe LinkedIn enrichment

Building personalized outreach requires accurate job history. The `get_linkedin_details` tool pulls this data directly into your Python application. Because you are using a type-safe framework, you know the job titles and company names will exist in the exact format your downstream systems expect. There is no silent corruption here. Your agent grabs the full profile using `get_lead_details`. It parses the response, validates the required fields, and safely injects the clean data into your CRM.

Bulletproof list management via MCP

Running out of credits mid-execution breaks automated workflows. Your code prevents this by calling `get_credit_balance` before starting a heavy prospecting loop. It parses the exact integer value and halts if the balance drops below your defined threshold. Managing the actual contacts is just as rigid. The agent queries `list_prospecting_lists` to find the correct target ID. It then pushes the validated contact using `add_new_lead`. If a bad record somehow makes it through, `delete_lead` removes it instantly.

Setup guide

Set up AeroLeads MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "aeroleads-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to AeroLeads tools.",
)

result = await agent.run("List recent AeroLeads transactions")
print(result.output)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AeroLeads. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about AeroLeads MCP in Pydantic AI

Install `pydantic-ai-slim[mcp]`. Pass your Vinkius endpoint to `MCPToolset` using the unified HTTP approach. Attach that toolset directly to your Agent instance.

That depends on your models. If you mark a phone number as required and `get_lead_details` omits it, the framework throws a validation error immediately.

Yes, the framework is entirely model-agnostic. You can route these tool calls through OpenAI, Anthropic, or a local Llama instance running on your machine.

Write a quick script that calls `list_team_members`. The agent fetches the user array and validates it against your expected team roster.

The Vinkius architecture relies on ephemeral V8 isolates. When your agent retrieves verified emails and job titles, that payload routes through a zero-trust sandbox. We never store or inspect your prospect lists.

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