Can I update the status of a work order through the agent?

Yes. The `update_order_status` tool allows your AI agent to change the lifecycle status of any service order (e.g., to 'InProgress' or 'Completed') so you can manage dispatching directly through chat.

How do I see the contact details for a field technician?

You can use the `get_employee_profile` tool. Simply provide the unique employee ID, and your agent will return their full profile details, including contact information and assigned skills.

Is it possible to list all service locations for a customer?

Absolutely. Using the `list_service_locations` tool, you can retrieve a list of all physical sites and addresses registered in your WorkWave instance, helping you coordinate where jobs need to be performed.

WorkWave MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: WorkWave
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect WorkWave through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to WorkWave "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in WorkWave?"
    )
    print(result.data)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About WorkWave MCP Server

Connect your WorkWave Service account to any AI agent and manage your field service operations through natural conversation.

Pydantic AI validates every WorkWave tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Service Orders — Browse and list all work requests, retrieve full details for specific orders, and update lifecycle statuses (e.g., InProgress, Completed)
Customer Accounts — List all field service accounts and retrieve comprehensive details including contact info, billing history, and service locations
Field Personnel — List all registered technicians and field staff, and retrieve profile details to check roles, skills, and contact info
Equipment Inventory — Monitor and audit managed assets and equipment used across your field service operations directly from your agent
Site Discovery — Retrieve physical service locations and job site addresses, including geographical coordinates for routing purposes
Operational Insights — Quickly find unique account, order, employee, and location IDs required for automated field service workflows
Health Monitoring — Verify the connectivity and status of your WorkWave API integration to ensure real-time data sync

The WorkWave MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect WorkWave to Pydantic AI via MCP

Follow these steps to integrate the WorkWave MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from WorkWave with type-safe schemas

Why Use Pydantic AI with the WorkWave MCP Server

Pydantic AI provides unique advantages when paired with WorkWave through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your WorkWave integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your WorkWave connection logic from agent behavior for testable, maintainable code

WorkWave + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the WorkWave MCP Server delivers measurable value.

Type-safe data pipelines: query WorkWave with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple WorkWave tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query WorkWave and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock WorkWave responses and write comprehensive agent tests

WorkWave MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect WorkWave to Pydantic AI via MCP:

get_account_details

Retrieves details for a specific customer account

get_api_health

Checks the health and connectivity of the WorkWave API integration

get_employee_profile

Retrieves profile details for a specific employee

get_order_details

Retrieves details for a specific service order

list_field_employees

Lists technicians and field staff registered in WorkWave

list_field_service_accounts

Lists customer accounts in the WorkWave Service platform

list_service_equipment

Lists managed equipment and assets used in field service

list_service_locations

Lists physical service locations and job sites

list_service_orders

Lists service orders and work requests

update_order_status

g. mark as Pending, InProgress, or Completed). Updates the lifecycle status of a service order

Example Prompts for WorkWave in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with WorkWave immediately.

"List all active service orders in WorkWave."

"Update order #ORD-101 status to 'InProgress'."

"Find the profile for technician ID 'tech-555'."

Troubleshooting WorkWave MCP Server with Pydantic AI

Common issues when connecting WorkWave to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

WorkWave + Pydantic AI FAQ

Common questions about integrating WorkWave MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your WorkWave MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.