How to Use the Hexomatic MCP in Pydantic AI

Q: How does Pydantic AI ensure data from a Hexomatic workflow is correct?

It validates the structure of the data returned by getworkflowresults against a predefined schema. If the data doesn't match the expected format—for instance, a field is missing or has the wrong type—it raises an error immediately.

Q: How do I find a workflow ID in Hexomatic to use with my Pydantic AI agent?

Have your agent call the listworkflows tool to get a complete dictionary of all available workflows and their corresponding IDs. The response is a typed object, so it's easy to iterate through.

Run Hexomatic automations with type-safe, validated outputs using Pydantic AI.

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Connect Hexomatic MCP to Pydantic AI

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Setup Hexomatic with Pydantic AI

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Get Data You Can Trust. Period.

When your agent calls `get_workflow_results`, Pydantic AI automatically validates the response. If a scraping recipe breaks and returns messy or incomplete data, your code doesn't just fail silently—it raises a `ValidationError` right away. This means you build on a solid foundation. No more defensive code checking for missing keys or wrong data types. If the call succeeds, you have a clean, typed Pydantic object. You can trust the data's structure, every time.

Manage Workflows with Confidence

This type-safety applies to every tool, not just data outputs. When you use `get_workflow_details` or check your balance with `get_account_usage`, the JSON response is parsed directly into a Pydantic model. You know exactly what fields to expect. This makes the agent's internal logic much cleaner and more robust. There's no guesswork involved in parsing the API responses from your MCP server.

Model-Agnostic Hexomatic Control

Pydantic AI doesn't lock you into a specific LLM. You can use OpenAI, Anthropic, Gemini, or a local model, and your Hexomatic integration won't change. The tools, like `run_workflow` and `search_workflows`, are defined independently of the model. This lets you swap out the brain of your agent without having to rewrite the parts that interact with Hexomatic. Your connection to this MCP server for web automation remains stable, letting you focus on picking the right model for the job.

Setup guide

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

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

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

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Common questions about Hexomatic MCP in Pydantic AI

It validates the structure of the data returned by `get_workflow_results` against a predefined schema. If the data doesn't match the expected format—for instance, a field is missing or has the wrong type—it raises an error immediately.

If the Hexomatic API call itself fails, Pydantic AI will raise an exception. If the call succeeds but returns an empty or error-formatted result, the Pydantic model validation will likely fail, alerting your agent that the data is not usable.

Yes. Pydantic AI is model-agnostic. You can configure it to use any compatible local model for reasoning, while still using the `MCPToolset` to connect to the Hexomatic server for performing actions.

Have your agent call the `list_workflows` tool to get a complete dictionary of all available workflows and their corresponding IDs. The response is a typed object, so it's easy to iterate through.

Your agent's requests, including any input data, are handled within Vinkius's V8 Isolate Sandboxes. These are single-use, memory-safe environments. The data, such as workflow results, is streamed back to your agent and is never stored on the Vinkius platform.

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