Can I move a candidate to a new stage using the agent?

Yes! Use the `move_candidate` tool with the Position ID, Candidate ID, and the target Stage ID. Your agent will update the pipeline status in Breezy HR instantly.

How do I list all the candidates for a specific job?

Simply ask the agent to `list_candidates` and provide the Position ID. It will retrieve the current applicants and their primary details.

Does the integration allow creating a new job position?

Yes. Use the `create_position` action and provide the name, description, and job type. The position will be created in your account as a draft or published based on your settings.

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

Name: Breezy HR
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

Connect your Breezy HR account to any AI agent and orchestrate your hiring and candidate management workflows through natural conversation.

When paired with CrewAI, Breezy HR becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Breezy HR 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

Position Oversight — List and retrieve detailed metadata for all your active and draft job positions.
Candidate Management — Create new candidate profiles, move them through your pipeline, and retrieve full applicant histories.
Pipeline Coordination — List and monitor stages for specific positions to ensure a smooth hiring flow.
Administrative Access — Retrieve company information and task templates straight from your workspace.

The Breezy HR 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 Breezy HR to CrewAI via MCP

Follow these steps to integrate the Breezy HR 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 Breezy HR

Why Use CrewAI with the Breezy HR MCP Server

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

Breezy HR + CrewAI Use Cases

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

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

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

Breezy HR MCP Tools for CrewAI (10)

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

create_candidate

Add a candidate to a position

create_position

Create a new job position

get_candidate

Get specific candidate details

get_company

Get details of the authenticated company

get_position

Get details of a specific position

list_candidates

List candidates for a specific position

list_positions

List all job positions

list_stages

List pipeline stages for a position

list_task_templates

List available task templates

move_candidate

Move a candidate to a different pipeline stage

Example Prompts for Breezy HR in CrewAI

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

"List all active job positions in Breezy HR."

"Show the candidates for the 'Senior Developer' role."

"Move candidate cand_123 to the 'Interview' stage."

Troubleshooting Breezy HR MCP Server with CrewAI

Common issues when connecting Breezy HR 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.

Breezy HR + CrewAI FAQ

Common questions about integrating Breezy HR 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.