How do I get JobNimbus API credentials?

Log in to your JobNimbus account, navigate to Settings > API, and click 'New API Key'.

Can I see my tasks and workflows?

Yes, this MCP provides tools to list both active tasks and configured workflows in your account.

Does it support payment tracking?

Yes, you can retrieve recent payments using the list_payments tool.

JobNimbus MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: JobNimbus
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="JobNimbus Specialist",
    goal="Help users interact with JobNimbus effectively",
    backstory=(
        "You are an expert at leveraging JobNimbus 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 JobNimbus "
        "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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About JobNimbus MCP Server

Empower your AI agents with JobNimbus's specialized CRM for contractors. This MCP server allows you to list and retrieve contacts and jobs, manage tasks and workflows, track payments, and view organization users directly through the JobNimbus API. Ideal for automating field service operations and project management.

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

The JobNimbus 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 JobNimbus to CrewAI via MCP

Follow these steps to integrate the JobNimbus 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 JobNimbus

Why Use CrewAI with the JobNimbus MCP Server

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

JobNimbus + CrewAI Use Cases

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

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

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

JobNimbus MCP Tools for CrewAI (10)

These 10 tools become available when you connect JobNimbus to CrewAI via MCP:

get_contact

Returns addresses, phone numbers, email, and custom fields. Use this for deep intelligence on a customer before an interaction. Retrieves details for a specific contact

get_job

Returns project descriptions, associated contact IDs, and current workflow status. Use this to analyze project specifics or provide an update on a job. Retrieves details for a specific job

list_boards

Useful for navigating the account structure. Lists all configured boards

list_contacts

Returns names, contact types, and IDs. Use this to identify clients or start a search for a specific customer. Lists all contacts in JobNimbus

list_jobs

Includes job titles, status, and IDs. Essential for monitoring project flow and upcoming work. Lists all jobs in JobNimbus

list_payments

Essential for monitoring revenue and project billing status. Lists all recent payments

list_products

Useful for auditing available services and pricing items. Lists all products and services

list_tasks

Returns task descriptions, due dates, and IDs. Use this to help the user manage their daily workload or audit team activities. Lists all tasks

list_users

Useful for identifying sales reps or project managers. Lists all users in the organization

list_workflows

Useful for understanding the steps in the company's business processes. Lists all configured workflows

Example Prompts for JobNimbus in CrewAI

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

"List all active contacts in JobNimbus."

"Show me the latest jobs created."

"Check the status of my active tasks."

Troubleshooting JobNimbus MCP Server with CrewAI

Common issues when connecting JobNimbus 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.

JobNimbus + CrewAI FAQ

Common questions about integrating JobNimbus 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.