How to Use the Formilla MCP in Pydantic AI

Q: How do I integrate Formilla with Pydantic AI?

Install the necessary dependencies and use MCPToolset to point to your server URL. Add the toolset to your agent configuration, and it will automatically validate all incoming tool responses.

Q: Can I update Formilla contacts through Pydantic AI?

Yes, the updatecontact tool allows for precise record modifications. Since it uses Pydantic models, you are guaranteed that your update payload matches the required API structure.

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Connect Formilla MCP to Pydantic AI

Create your Vinkius account to connect Formilla 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 Formilla with Pydantic AI

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Type-safe contact operations

Every response from `get_contact` or `search_contacts` is validated against your Pydantic models. If the API returns unexpected types, your agent catches the issue immediately. You use `upsert_contact` to keep your CRM in sync with your agent's findings. The schema enforcement ensures your database remains clean and predictable.

Pydantic AI conversation management

Your agent pulls chat data using `list_conversations`. Because the output is validated, you never deal with missing fields or corrupt message history. `get_conversation` provides the full context of a chat. The agent can then process this structured data to extract intent or sentiment without manual parsing.

Visitor monitoring and segmentation

The `list_visitors` tool gives your agent a snapshot of who is on your site. This data is validated at runtime to ensure the agent acts on correct information. Use `list_segments` to retrieve your current audience categories. Your agent uses these to filter and prioritize its responses based on the visitor's segment status.

Setup guide

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

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

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

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Common questions about Formilla MCP in Pydantic AI

Install the necessary dependencies and use `MCPToolset` to point to your server URL. Add the toolset to your agent configuration, and it will automatically validate all incoming tool responses.

The framework will raise a validation error immediately. This prevents your agent from making decisions based on malformed contact or chat records.

It is model-agnostic. You can switch between OpenAI, Anthropic, or Gemini, and your Formilla tool validation logic remains consistent.

Security is enforced through strict schema validation and local processing. Your agent only accesses specific contact identifiers and message logs, which are never stored by the server itself.

Yes, the `update_contact` tool allows for precise record modifications. Since it uses Pydantic models, you are guaranteed that your update payload matches the required API structure.

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