How to Use the Gallabox MCP in Pydantic AI

Q: How do I configure Gallabox with Pydantic AI?

Install pydantic-ai-slimmcp. Define your MCPToolset using your Vinkius HTTP URL, and pass it in the toolsets array when building your Agent. Do not use the deprecated MCPServerHTTP class.

Q: Does Pydantic AI validate Gallabox template variables?

Yes. When the agent uses listmessagetemplates and then attempts to send one, Pydantic AI ensures the payload matches the expected schema. Validation errors prevent malformed requests.

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Connect Gallabox MCP to Pydantic AI

Create your Vinkius account to connect Gallabox 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 Gallabox with Pydantic AI

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Perplexity

Type-safe WhatsApp messaging

Calling `send_whatsapp_template` through Pydantic AI guarantees that your agent provides the exact parameters required by the API. If the LLM hallucinates a missing template variable, the framework throws a validation error immediately. Pass `MCPToolset` to your Agent to initialize this. The framework handles the Streamable HTTP transport and maps every tool input to strict Pydantic schemas. It fails loudly if the model tries anything stupid.

Validate chat data instantly

When your agent calls `list_active_chats` or `get_chat_details`, it expects a specific JSON structure. Pydantic AI enforces this contract. You never have to worry about silent data corruption creeping into your downstream logic. This strictness applies across all read operations. Pulling records with `list_whatsapp_contacts` results in clean, validated objects. You write your business logic knowing the data shape is guaranteed.

Pydantic AI MCP Server routing

Building escalation logic requires accurate team data. The `list_support_teams` tool gives your agent the exact IDs needed to hand off a conversation. Because Pydantic AI is model-agnostic, you can swap between Anthropic for complex routing and a fast local model for simple tasks like `verify_api_connection`. The tool schemas remain identical regardless of the underlying LLM.

Setup guide

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

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

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

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Common questions about Gallabox MCP in Pydantic AI

Install `pydantic-ai-slim[mcp]`. Define your `MCPToolset` using your Vinkius HTTP URL, and pass it in the `toolsets` array when building your Agent. Do not use the deprecated `MCPServerHTTP` class.

Yes. When the agent uses `list_message_templates` and then attempts to send one, Pydantic AI ensures the payload matches the expected schema. Validation errors prevent malformed requests.

The framework is completely model-agnostic. You can pipe the output of `list_thread_messages` into an OpenAI, Gemini, or local Ollama model without changing your tool configuration.

Pydantic AI catches it. If an MCP Server returns an unmapped status code during a `get_contact_details` call, the framework fails loudly. You get a clear traceback instead of weird runtime bugs.

This service accesses raw WhatsApp message content and personal contact details. Every transaction executes within a strictly isolated, ephemeral sandbox. Vinkius requires only a single endpoint token, ensuring your credentials never leak into the application state.

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