How to Use the Greenhouse MCP in CrewAI

Deploy a specialized recruitment crew using CrewAI. Automate candidate sourcing and pipeline auditing with autonomous agents.

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Connect Greenhouse MCP to CrewAI

Create your Vinkius account to connect Greenhouse 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 Greenhouse with CrewAI

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Perplexity

Autonomous candidate research

Assign an agent to monitor the pipeline using `list_candidates`. It can identify top applicants and pull their details via `get_candidate`. This frees up your recruiters for face-to-face interviews. The agent handles the heavy lifting of data gathering.

Collaborative hiring audit

Run a crew where one agent lists jobs and another audits them for completeness. Use `list_jobs` and `get_job` to compare roles against current needs. It finds gaps in your hiring strategy. The team approach ensures no detail gets missed during your review.

Hierarchical pipeline response

Structure your crew so a moderator agent validates actions before calling `create_candidate`. It adds a layer of oversight to your automation. This setup works for large-scale hiring. You maintain control while the agents handle the repetitive tasks.

Setup guide

Set up Greenhouse 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 Greenhouse tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Greenhouse 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="Greenhouse Analyst",
        goal="Access and analyze Greenhouse data via MCP.",
        backstory="Expert analyst with direct Greenhouse access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Greenhouse 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 Greenhouse. 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 Greenhouse MCP in CrewAI

Absolutely. You can assign specific agents to watch the pipeline and report back on candidate status.

It works natively. You pass the server URL to your agent's configuration and the tools become available immediately.

They are. Agents use the tools to query the ATS, providing them with the context needed to make informed decisions.

Yes. You can apply tool filters to restrict your agents to specific operations. This keeps your pipeline secure.

The server enforces standard auth. Your data is isolated and only accessible to the agents you explicitly authorize.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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