How to Use the WorkflowMax MCP in Pydantic AI

Q: How does WorkflowMax and Pydantic AI handle client data? Is it safe?

When your agent calls getclient, the response is immediately validated against a schema. If the underlying API returns bad data, your system fails loud with an explicit error.

Q: What if I need to list all jobs? Does WorkflowMax and Pydantic AI support it?

Yes, the listjobs tool pulls a list of job records. Every field in that returned data is type-checked, giving you confidence in your pipeline.

Q: Can I list tasks? Is that part of the MCP Server's capability?

Yep. The listtasks tool gives you a clean, predictable list of service units. This keeps your time logging accurate and type-safe.

Use WorkflowMax to manage data with type safety via Pydantic AI.

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Connect WorkflowMax MCP to Pydantic AI

Create your Vinkius account to connect WorkflowMax 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 WorkflowMax with Pydantic AI

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Creating and validating new clients using WorkflowMax MCP Server

To start a client, the agent calls `create_client` with the required name. Because of Pydantic validation, you're guaranteed that the resulting object structure is exactly what your code expects. Need to add contact info? The `create_client_contact` tool requires specific details for both the UUID and the contact fields, preventing junk data from entering the system.

Managing time tracking with WorkflowMax MCP Server

The agent uses `create_timesheet` to log work. It needs three defined types: Job UUID, Task UUID, and duration/hours—all validated at runtime. Auditing is reliable because the `list_timesheets` tool provides clean, predictable data structures for every logged entry.

Getting accurate project details via WorkflowMax MCP Server

The agent can pull job details using `get_job`, ensuring that fields like start date and client ID are returned in the exact format your Pydantic models need. The server also provides `list_jobs` for a full, validated overview. If you must change something, `update_job` handles modifications while maintaining strict type compliance.

Setup guide

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

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

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

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Common questions about WorkflowMax MCP in Pydantic AI

When your agent calls `get_client`, the response is immediately validated against a schema. If the underlying API returns bad data, your system fails loud with an explicit error.

Yes, the `list_jobs` tool pulls a list of job records. Every field in that returned data is type-checked, giving you confidence in your pipeline.

You must provide the client UUID along with the contact details to `create_client_contact`. The process requires all inputs to match expected data types for successful validation.

Yep. The `list_tasks` tool gives you a clean, predictable list of service units. This keeps your time logging accurate and type-safe.

The server handles Client IDs, Job UUIDs, Contact details, Task UUIDs, and timesheet entries, all of which are validated to ensure maximum data integrity for your application.

Use it with your favorite AI tools

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

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