How to Use the Dalil AI MCP in Pydantic AI

Enforce strict schema validation for Dalil AI tools in Pydantic AI.

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Connect Dalil AI MCP to Pydantic AI

Create your Vinkius account to connect Dalil AI 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 Dalil AI with Pydantic AI

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Claude

Perplexity

Type-safe contact handling in Pydantic AI

Every response from `list_contacts` hits your Pydantic models first. If the API structure shifts, your agent halts before bad data ruins your state. This is for when you need to be sure. You get clean objects every time.

Validate messaging in Pydantic AI

Use `send_linkedin_message` with your defined schemas. Your agent must match the required fields or the tool won't fire. It stops hallucinations. If the agent tries to send incomplete data, the validation layer catches it.

Query signals with Pydantic AI

Call `get_contact_signals` and map the output to a typed structure. You turn raw signals into actionable logic for your agent. This removes ambiguity. Your agent works with data it can actually understand.

Setup guide

Set up Dalil AI 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": {
        "dalil-ai-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Dalil AI MCP in Pydantic AI

It enforces runtime checks. Your agent fails loudly if the API returns unexpected data, preventing silent errors.

It is. You can swap your underlying model while keeping the same tool definitions and validation logic.

Install the slim package and pass the URL to the toolset. The framework handles the connection automatically.

It does. The toolset is designed for async execution, so your agent stays responsive under load.

Signal data is transient. We process the request and pass it to your agent, ensuring no sensitive lead metrics remain on our side.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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Pydantic AI sdk-python

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