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 CrewAI 10 tools — connect in under 2 minutes

Name: WorkWave
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to WorkWave through Vinkius, pass the Edge URL in the `mcps` parameter and every WorkWave tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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

from crewai import Agent, Task, Crew

agent = Agent(
    role="WorkWave Specialist",
    goal="Help users interact with WorkWave effectively",
    backstory=(
        "You are an expert at leveraging WorkWave tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in WorkWave "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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IAMAccess control

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Ed25519Audit chain

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

When paired with CrewAI, WorkWave becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call WorkWave tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

Follow these steps to integrate the WorkWave MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from WorkWave

Why Use CrewAI with the WorkWave MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with WorkWave through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

WorkWave + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries WorkWave for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries WorkWave, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain WorkWave tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries WorkWave against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

WorkWave MCP Tools for CrewAI (10)

These 10 tools become available when you connect WorkWave to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

WorkWave + CrewAI FAQ

Common questions about integrating WorkWave MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.