How to Use the LeadsRx MCP in Pydantic AI

Q: How do I connect the LeadsRx MCP Server to a Pydantic AI agent?

Use the unified MCPToolset pointing to your Vinkius HTTP URL to expose the MCP Server to your Pydantic AI Agent constructor. This exposes all ten tools, including listchannels, to your type-safe agent without manual schema definitions.

Q: Can I use Pydantic AI to validate LeadsRx campaign lists?

Yes, when your agent calls listcampaigns, the Pydantic AI framework validates the array of campaigns against the tool's output schema. You can safely map the validated fields straight to your internal data models.

Q: How do I list connected LeadsRx marketing agencies using Pydantic AI?

Call listagencies through the toolset in Pydantic AI. The agent receives a validated list of agency profiles, allowing you to filter and sort them using standard Python type hints.

Run type-safe LeadsRx marketing attribution queries in Pydantic AI with strict schema validation.

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Connect LeadsRx MCP to Pydantic AI

Create your Vinkius account to connect LeadsRx 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 LeadsRx with Pydantic AI

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Validate LeadsRx campaign results in Pydantic AI

The `get_campaign_results` tool returns LeadsRx attribution metrics that Pydantic AI validates against strict Python type schemas. This guarantees that LeadsRx campaign spend and conversion counts are parsed as exact floats and integers in Pydantic AI. If the LeadsRx API returns unexpected data formats, your Pydantic AI agent fails immediately instead of processing corrupted metrics. Your app avoids making incorrect budget recommendations based on malformed LeadsRx data.

Track touchpoints with this type-safe MCP Server

The `list_touchpoints` tool provides a structured list of LeadsRx customer interactions directly to your Pydantic AI agent. Each touchpoint is validated by Pydantic AI to ensure it contains a valid timestamp and channel type. Your Pydantic AI agent uses `get_touchpoint_details` to inspect individual customer journeys. Because the schema is enforced at runtime by Pydantic AI, you can write clean logic to filter out LeadsRx journeys that lack critical tracking parameters.

Write LeadsRx conversions with Pydantic AI

The `add_conversion` tool sends new transaction events from your Pydantic AI agent to the LeadsRx platform. The Pydantic AI tool schema enforces that every required field is present before the payload leaves your application for LeadsRx. You can query `list_conversions` inside Pydantic AI to confirm the event was registered correctly. Pydantic AI parses the response, making it easy to build automated testing pipelines for your LeadsRx conversion tracking scripts.

Setup guide

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

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

result = await agent.run("List recent LeadsRx 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 LeadsRx. 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 LeadsRx MCP in Pydantic AI

Use the unified `MCPToolset` pointing to your Vinkius HTTP URL to expose the MCP Server to your Pydantic AI Agent constructor. This exposes all ten tools, including `list_channels`, to your type-safe agent without manual schema definitions.

The Pydantic AI framework raises a validation error immediately when querying tools like `get_conversion_details`. This prevents silent failures, ensuring your agent never operates on incomplete LeadsRx conversion data.

Yes, when your agent calls `list_campaigns`, the Pydantic AI framework validates the array of campaigns against the tool's output schema. You can safely map the validated fields straight to your internal data models.

Call `list_agencies` through the toolset in Pydantic AI. The agent receives a validated list of agency profiles, allowing you to filter and sort them using standard Python type hints.

Your LeadsRx conversion record and agency profile data are processed using Vinkius's zero-trust V8 isolate sandbox. Pydantic AI only receives the validated JSON payloads over an encrypted transport, keeping your raw API tokens hidden from the MCP connection.

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