How to Use the 360dialog MCP in Pydantic AI

Build type-safe WhatsApp messaging agents with Pydantic AI and the 360dialog MCP Server.

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Connect 360dialog MCP to Pydantic AI

Create your Vinkius account to connect 360dialog 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 360dialog with Pydantic AI

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Perplexity

Type-validated 360dialog tools for Pydantic AI

Every tool response from the server is checked against Pydantic models. If `get_template` returns unexpected fields, your agent crashes immediately rather than processing bad data. This rigor prevents silent failures in your communication pipeline. You gain total confidence that your message structure matches the API requirements.

Strict messaging in Pydantic AI

Call `send_message` with confidence that your data types are correct. Pydantic AI validates the recipient number format before the tool ever hits the network. This eliminates common errors where a string might be passed as an integer or vice-versa. Your agent handles the communication lifecycle with strict schema enforcement.

Template management for Pydantic AI

Use `list_templates` to populate your agent's selection logic with validated data structures. It ensures your agent only selects templates that exist in your 360dialog account. Validation errors appear during the tool call phase. You catch issues with template names or language codes before the message is ever dispatched.

Setup guide

Set up 360dialog 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": {
        "360dialog-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to 360dialog tools.",
)

result = await agent.run("List recent 360dialog 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 360dialog. 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 360dialog MCP in Pydantic AI

You use the MCPToolset class, passing in your Vinkius server URL. This connects your agent directly to the tools, which are then validated against your defined models.

The server supports SSE and Streamable HTTP. You configure your toolset to point at the Vinkius endpoint, and Pydantic AI handles the transport layer.

Yes, if a tool call fails, the framework raises an exception based on the server's response. You can handle these errors using standard Python try-except blocks.

You do not store keys in your code. Vinkius handles the authentication via an endpoint token, keeping your sensitive access data out of the agent's memory space.

The system ensures strict data typing for all message metadata. Vinkius provides an ephemeral connection, so no persistent storage of your message content exists on the server.

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