How do I obtain my Fieldly API credentials?

First, contact support@fieldly.com to enable the Public API. Once activated, you can find your Client ID and Client Secret in the **Integration Settings** of your Fieldly Admin panel.

How long is the access token valid?

Fieldly access tokens are valid for one hour. The agent handles token renewal automatically so you don't have to worry about manual updates.

Can I create new construction tasks via chat?

Yes! The `create_work_item` tool allows you to programmatically generate new construction tasks and work items directly within your AI-powered workflow flawlessy.

Fieldly MCP Server for CrewAI 11 tools — connect in under 2 minutes

Name: Fieldly
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 11 Tools Framework

Connect your CrewAI agents to Fieldly through Vinkius, pass the Edge URL in the `mcps` parameter and every Fieldly 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

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Fieldly Specialist",
    goal="Help users interact with Fieldly effectively",
    backstory=(
        "You are an expert at leveraging Fieldly 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 Fieldly "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 11 available tools "
        "and what they can do."
    ),
)

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

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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 Fieldly MCP Server

Fieldly is a specialized project management platform for the construction industry. This MCP server allows your AI agent to interact with your Fieldly account flawlessly.

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

Key Features

Work Item Orchestration — List all construction tasks and work items, and fetch detailed metadata natively.
Booking Intelligence — Retrieve and inspect scheduling bookings to stay updated on team allocation flawlessly.
Invoice Management — Access billing data and individual invoices to track project financials flawlessly.
Article Access — Query your catalog of articles, materials, and service items natively.
Customer CRM — Access customer profiles and contact details to manage business relationships flawlessly.
Identity Verification — Verify the authorized application and user profile through the agent flawlessly.

The Fieldly MCP Server exposes 11 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 Fieldly to CrewAI via MCP

Follow these steps to integrate the Fieldly 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 11 tools from Fieldly

Why Use CrewAI with the Fieldly MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Fieldly 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

Fieldly + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Fieldly 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 Fieldly, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Fieldly 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 Fieldly against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Fieldly MCP Tools for CrewAI (11)

These 11 tools become available when you connect Fieldly to CrewAI via MCP:

create_work_item

Create a new work item

get_booking

Get details for a specific booking

get_invoice

Get details for a specific invoice

get_me

Get details for the authorized application/user

get_work_item

Get details for a specific work item

list_articles

List all inventory and service articles

list_bookings

List all scheduling bookings

list_customers

List all customers

list_invoices

List all invoices

list_users

List all users in the system

list_work_items

List all work items (jobs/tasks)

Example Prompts for Fieldly in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Fieldly immediately.

"List all active work items in Fieldly."

"Show me the team bookings for tomorrow."

"Check for any unpaid construction invoices."

Troubleshooting Fieldly MCP Server with CrewAI

Common issues when connecting Fieldly 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.

Fieldly + CrewAI FAQ

Common questions about integrating Fieldly 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.