How to Use the HrFlow.ai MCP in CrewAI

Q: How do I add HrFlow.ai to my CrewAI agent configuration?

Simply pass the server URL into the mcps parameter of your agent definition. CrewAI handles the connection and exposes the tools automatically.

Q: Can I filter which HrFlow.ai tools my CrewAI agents access?

You can use the toolfilter option in your CrewAI setup to restrict agents to specific tools. This ensures your sourcing agent only accesses the search functions it actually needs.

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Connect HrFlow.ai MCP to CrewAI

Create your Vinkius account to connect HrFlow.ai to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup HrFlow.ai with CrewAI

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Specialized recruiting agents for CrewAI

Assign one agent to research candidates with `search_profiles` while another analyzes their fit with `score_profiles`. This role-based setup lets your crew divide and conquer the hiring process. Each agent shares memory, so they know exactly what the other found. It removes the bottleneck of one person managing the entire applicant pool.

Autonomous sourcing with HrFlow.ai and CrewAI

Let your sourcing agent monitor your job boards using `list_jobs` and `search_jobs`. When it finds a match, it can autonomously begin the parsing process for you. Your team wakes up to a pre-screened list of candidates. It turns a manual, day-long task into a background process that runs while you sleep.

Deep profile insights for CrewAI agents

Give your agents the ability to run `ask_profile` to query candidate experience in plain English. They can reason through years of work history to identify hidden gems. This creates a more nuanced view of every applicant. The agents report back with a clear summary, saving you from reading dozens of resumes yourself.

Setup guide

Set up HrFlow.ai MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke HrFlow.ai tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="HrFlow.ai Analyst",
    goal="Access and analyze HrFlow.ai data via MCP.",
    backstory="Expert analyst with direct HrFlow.ai access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent HrFlow.ai transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="HrFlow.ai Analyst",
        goal="Access and analyze HrFlow.ai data via MCP.",
        backstory="Expert analyst with direct HrFlow.ai access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent HrFlow.ai transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by HrFlow.ai. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about HrFlow.ai MCP in CrewAI

Simply pass the server URL into the `mcps` parameter of your agent definition. CrewAI handles the connection and exposes the tools automatically.

You can use the tool_filter option in your CrewAI setup to restrict agents to specific tools. This ensures your sourcing agent only accesses the search functions it actually needs.

It does. You can connect to multiple instances if you manage different hiring environments, allowing your crew to pull data from various sources simultaneously.

Use a moderator agent to coordinate the output of your other agents. This keeps the workflow orderly and ensures the final candidate report is accurate.

The server uses ephemeral sessions for every request. No resume data is cached between agent turns, ensuring your candidate information is protected at every step of the team's collaboration.

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