How to Use the JobScore MCP in CrewAI

Q: Does CrewAI support custom candidate sources from JobScore?

Yes, your agents can call listsources to determine if a candidate came from LinkedIn, Glassdoor, or a referral. The crew uses this context to tailor its screening notes.

Deploy a crew of specialized AI agents to source, screen, and match JobScore candidates using CrewAI and the JobScore MCP Server.

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Connect JobScore MCP to CrewAI

Create your Vinkius account to connect JobScore 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 JobScore with CrewAI

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Set up a digital recruiting department

The `list_candidates` tool feeds raw applicant lists into your CrewAI hiring workspace. One agent screens the incoming list, while a second agent uses `get_candidate` to analyze resume highlights for specific technical skills. These specialized agents collaborate using shared memory to prevent double-screening. Your team gets a curated list of top-tier applicants without spending hours clicking through the ATS interface.

Match candidates to roles with this MCP Server

The `get_job` tool provides your CrewAI agents with complete lists of requirements and hiring managers for any open position. Your matching agent compares these requirements against candidate records to score applicant relevance. You configure this pipeline by passing the Vinkius server URL directly to the agent's parameters. The crew runs autonomously in the background, flagging high-match candidates as they apply.

Analyze regional hiring patterns

The `list_locations` tool allows your analytical agents to group open positions by physical office or remote region. Another agent combines this with `list_departments` to map head-count allocation across the entire company. This collaborative analysis helps HR teams spot hiring bottlenecks. You receive clean, structured reports summarizing which regions need recruiter support.

Setup guide

Set up JobScore 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 JobScore tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

You pass the secure Vinkius URL directly in the agent's MCP configuration. CrewAI automatically discovers and exposes tools like `get_candidate` to that specific agent.

Yes, your agents can call tools in parallel during hierarchical or sequential tasks. Vinkius handles the concurrent requests safely without dropping connections.

Yes, your agents can call `list_sources` to determine if a candidate came from LinkedIn, Glassdoor, or a referral. The crew uses this context to tailor its screening notes.

You use the MCP server settings class from CrewAI and define a tool filter. This prevents a screening agent from accessing sensitive administrative tools like `list_users`.

All data transit occurs over encrypted channels directly between CrewAI and the Vinkius secure gateway. Candidate profiles and team rosters are processed entirely in memory and are never written to persistent disk.

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