How to Use the Greenhouse Alternative MCP in CrewAI

Q: How do I filter tools for this Greenhouse Alternative in CrewAI?

Use the toolfilter option in your MCP configuration. This lets you expose only the specific tools, like list or get, that your agents require for their assigned tasks.

Deploy a specialized agent crew to manage your hiring pipeline. Greenhouse Alternative power for autonomous CrewAI operations.

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Connect Greenhouse Alternative MCP to CrewAI

Create your Vinkius account to connect Greenhouse Alternative 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 Alternative with CrewAI

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Specialized recruiting crews in CrewAI

Assign one agent to source candidates and another to manage application status. By using `list_board_departments` and `get_board_job`, your crew can identify high-priority roles that need immediate attention. Agents collaborate by sharing the context of each candidate. The research agent finds the talent, and the acting agent submits them using `submit_board_application`.

Autonomous pipeline maintenance in CrewAI

Set up a monitor agent to audit your ATS data. Using `get_audit_log_events` and `list_applications`, the agent detects discrepancies and fixes them via `update_application` without you lifting a finger. Your pipeline stays accurate and up-to-date around the clock. It’s like having a dedicated recruiting coordinator working every hour of the day.

Full-cycle hiring automation in CrewAI

Create a hierarchical crew that handles the end-to-end process. From listing jobs with `list_board_jobs` to vetting candidates via `get_candidate_activity_feed`, the agents handle the heavy lifting. You define the roles and the goal. The crew executes the steps and provides a final report on what was accomplished in the ATS.

Setup guide

Set up Greenhouse Alternative 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 Alternative tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Greenhouse Alternative 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 →

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Common questions about Greenhouse Alternative MCP in CrewAI

Absolutely. You pass the server URL directly to your agent's MCP configuration, and it will immediately gain the ability to call any of the 16 recruiting tools.

It is. Because the server tools are granular, you can limit your agents to only the operations they need, preventing unauthorized changes to your candidate data.

Use the tool_filter option in your MCP configuration. This lets you expose only the specific tools, like list or get, that your agents require for their assigned tasks.

Yes. Agents can share the results of tool calls through their shared memory, allowing the entire crew to act on the same candidate data.

All data interactions happen through an ephemeral V8 sandbox. The server only accesses the specific application status and job board data required for the agent to complete its current task.

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