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How to Use the Icypeas MCP in Pydantic AI

Use Pydantic AI with Icypeas to enforce strict data validation on your lead generation and email verification workflows.

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Pydantic AI

Connect Icypeas MCP to Pydantic AI

Create your Vinkius account to connect Icypeas 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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Type-Safe Lead Retrieval for Pydantic AI

Every response from `list_prospects` or `search_prospects` is validated against your Pydantic models at runtime. If the API returns malformed data, your agent catches the issue immediately instead of proceeding with bad information. This ensures that your agent code remains stable and predictable. You define the schema, and Pydantic AI enforces it, giving you confidence that your lead data is always in the correct format.

Verified Outreach Cycles in Pydantic AI

Integrate `verify_email` into your agents to guarantee that only valid contact data moves forward. Pydantic AI validates the tool output, ensuring your agent logic only processes verified, deliverable email addresses. This prevents silent failures where invalid data might otherwise pollute your downstream systems. You get a clean, validated stream of prospects ready for your sales funnel.

Resource Management for Pydantic AI

Use `get_credits` to check your account status before executing expensive operations. Because Pydantic AI handles the response, you can easily map your credit balance to a typed object in your agent's state. This keeps your application logic clean and avoids unexpected errors during high-volume operations. Your agent stays informed about its capacity, allowing for graceful handling of credit limits.

Setup guide

Set up Icypeas MCP in Pydantic AI

Prerequisites

  • Python 3.10+ installed
  • pydantic-ai-slim[fastmcp] package
  • Active Vinkius subscription with a valid endpoint token
  1. 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. 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. 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": {
        "icypeas-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Icypeas. 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 Icypeas MCP in Pydantic AI

Pydantic AI validates every tool response against your defined models. If the Icypeas data doesn't match your schema, the agent will raise a validation error before any code executes.
Yes. You can chain `find_email` and `verify_email` within your agent's tools. Pydantic AI ensures that the output from the first tool is correctly passed to the next.
Call `get_campaign` and map the output to a Pydantic model. This gives you a structured way to inspect your outreach performance and adjust your agent's strategy.
Absolutely. The `list_prospect_lists` tool returns a structured list that Pydantic AI can parse automatically, making it easy to select the right list for your current task.
Security is built into the transport layer. We do not store or log your prospect emails, and the Pydantic AI framework ensures that data is only held in memory during the execution of your agent's task.

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