How to Use the ApplicantStack MCP in CrewAI

Q: How to link ApplicantStack to a CrewAI crew?

Pass the server URL directly into your agent's mcps list. The agents will then be able to use the ApplicantStack tools for their assigned tasks.

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Connect ApplicantStack MCP to CrewAI

Create your Vinkius account to connect ApplicantStack 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 ApplicantStack with CrewAI

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ApplicantStack research for CrewAI crews

Assign a research agent to scan your pipeline using `list_candidates`. It gathers necessary info and passes it to an analysis agent for review. The agents share memory, so your research agent doesn't need to repeat `get_candidate` calls. They collaborate to build a full profile of the hiring backlog.

CrewAI agents executing ApplicantStack actions

Let your moderator agent move candidates through stages using `update_candidate`. You define the criteria, and the crew handles the execution. You keep full control by filtering which tools each agent can access. The moderator gets write permissions, while the researcher only gets read access.

Monitor hiring with CrewAI

Task a monitor agent with calling `list_hires` every hour to report on new additions. It flags any inconsistencies for your review. This keeps your hiring operations running without human intervention. The crew detects changes and updates your internal records using the provided toolset.

Setup guide

Set up ApplicantStack 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 ApplicantStack tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Pass the server URL directly into your agent's `mcps` list. The agents will then be able to use the ApplicantStack tools for their assigned tasks.

They can. Using shared memory, one agent can fetch data with `list_jobs` and pass the results to another agent for processing.

It does. You can give the manager agent access to all tools, while subordinate agents only get specific read-only access to candidate info.

Your connection uses a single endpoint token provided by Vinkius. The communication is isolated within the sandbox to prevent unauthorized access.

The agents read candidate names and status flags through the MCP interface. This data is ephemeral and is cleared as soon as the agent task completes.

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