How to Use the FindThatLead MCP in Pydantic AI

Q: How do I install and set up FindThatLead with Pydantic AI?

Run pip install "pydantic-ai-slimmcp" and initialize MCPToolset with your HTTP endpoint. Pass this toolset directly into your Agent constructor to make all 12 MCP tools available.

Q: Can my agent manage leads using FindThatLead and Pydantic AI?

Yes, your agent can use createlead, getlead, and deletelead to manage your prospect lists. Every lead object returned is validated against strict TypeAdapter schemas before your code executes.

Build ultra-reliable lead generation workflows to validate every email and campaign from this FindThatLead MCP Server.

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Connect FindThatLead MCP to Pydantic AI

Create your Vinkius account to connect FindThatLead 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 FindThatLead with Pydantic AI

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Validate email searches at runtime with Pydantic AI

The `email_finder` tool retrieves the direct email address for a specific person based on their name and company domain. Pydantic AI enforces strict typing on the returned payload, ensuring your agent never processes malformed data. If the API returns unexpected field formats, the framework raises a validation error immediately. This prevents your agent from passing corrupt data down to your database or CRM.

Monitor campaign health with this type-safe MCP Server

The `get_campaign` tool fetches detailed performance metrics for your outbound email campaigns. The agent uses this data to verify open rates, click rates, and bounce statistics against your internal performance benchmarks. By calling `list_campaigns`, your agent can compare active campaigns and flag those with high bounce rates. This allows you to pause failing sequences before they damage your domain's sender authority.

Verify email deliverability with zero silent failures

The `email_verifier` tool checks the status of any email address to confirm if it is safe to send to. Pydantic AI parses this verification status, guaranteeing that the deliverability rating matches your strict schema. Your agent can then safely run `create_lead` to save only the verified contacts to your list. This strict validation pipeline ensures that unverified or risky emails never enter your active outbound sequences.

Setup guide

Set up FindThatLead 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": {
        "findthatlead-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about FindThatLead MCP in Pydantic AI

Run `pip install "pydantic-ai-slim[mcp]"` and initialize `MCPToolset` with your HTTP endpoint. Pass this toolset directly into your Agent constructor to make all 12 MCP tools available.

Pydantic AI will fail loudly by raising a validation error at runtime. This prevents silent failures and ensures your agent never writes corrupt email or campaign data to your production database.

Yes, your agent can use `create_lead`, `get_lead`, and `delete_lead` to manage your prospect lists. Every lead object returned is validated against strict TypeAdapter schemas before your code executes.

Yes, the toolset integrates with Pydantic AI's async execution loop. Your agent can run multiple `domain_search` queries concurrently without blocking your main application thread.

Your API token is stored securely and injected only at runtime inside an ephemeral V8 sandbox. No lead lists, verification records, or campaign details are saved, ensuring compliance with enterprise security requirements when using this MCP Server.

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