How do I get Jobtoolz API credentials?

Log in to your Jobtoolz account, navigate to Settings > API, and find your API Key.

Does it support departments and locations?

Yes, you can list all configured departments and office locations using this MCP.

Can I see pipeline stages?

Yes, the list_stages tool provides access to your recruitment pipeline configuration.

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

Name: Jobtoolz
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Jobtoolz through the Vinkius — pass the Edge URL in the `mcps` parameter and every Jobtoolz 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="Jobtoolz Specialist",
    goal="Help users interact with Jobtoolz effectively",
    backstory=(
        "You are an expert at leveraging Jobtoolz 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 Jobtoolz "
        "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 Jobtoolz MCP Server

Empower your AI agents with Jobtoolz's recruitment management platform. This MCP server allows you to list jobs, track candidates, manage pipeline stages, and view departments and locations directly through the Jobtoolz API. Ideal for automating hiring workflows and candidate engagement.

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

The Jobtoolz 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 Jobtoolz to CrewAI via MCP

Follow these steps to integrate the Jobtoolz 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 Jobtoolz

Why Use CrewAI with the Jobtoolz MCP Server

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

Jobtoolz + CrewAI Use Cases

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

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

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

Jobtoolz MCP Tools for CrewAI (10)

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

get_candidate

Returns contact details, application history, and custom field values. Use this for deep-dive vetting of an applicant. Retrieves details for a specific candidate

get_job

Returns descriptions, requirements, and internal status. Essential for detailed analysis of a specific role. Retrieves details for a specific job

list_candidates

Includes candidate names, IDs, and current pipeline status. Use this to monitor applicant flow and identify recent entries. Lists all candidates

list_departments

Useful for filtering jobs and candidates by business unit (e.g., Sales, R&D). Lists all departments

list_jobs

Returns job titles, IDs, and departments. Use this to identify open positions and locate job IDs for candidate management. Lists all active jobs

list_locations

Useful for identifying jobs in specific geographical regions. Lists all office locations

list_sources

g., "Company Website", "Indeed") configured in Jobtoolz. Useful for auditing the origins of candidate traffic. Lists all recruitment sources

list_stages

g., "Applied", "Interview", "Offer"). Essential for understanding the company's hiring process. Lists all configured pipeline stages

list_tags

Useful for identifying valid tags before performing a tagged search. Lists all configured tags

list_users

Useful for identifying account administrators or hiring managers. Lists all organization users

Example Prompts for Jobtoolz in CrewAI

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

"List all open jobs in Jobtoolz."

"Show me the details for candidate ID '123'."

"Check the available recruitment sources."

Troubleshooting Jobtoolz MCP Server with CrewAI

Common issues when connecting Jobtoolz 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

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

Jobtoolz + CrewAI FAQ

Common questions about integrating Jobtoolz 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.