How do I get JobScore API credentials?

Log in to your JobScore account, navigate to Admin > Integrations, and generate a Personal Access Token.

Does it support departments and locations?

Yes, you can list all configured departments and office locations using this MCP.

Can I see candidate details?

Yes, the list_candidates and get_candidate tools provide access to your applicant data.

JobScore MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: JobScore
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to JobScore through Vinkius, pass the Edge URL in the `mcps` parameter and every JobScore tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="JobScore Specialist",
    goal="Help users interact with JobScore effectively",
    backstory=(
        "You are an expert at leveraging JobScore tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in JobScore "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

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

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About JobScore MCP Server

Empower your AI agents with JobScore's comprehensive applicant tracking system. This MCP server allows you to list and retrieve job postings, track candidates, manage hiring teams and departments, and view hiring sources directly through the JobScore API. Ideal for automating recruitment workflows and talent acquisition.

When paired with CrewAI, JobScore becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call JobScore tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

The JobScore MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect JobScore to CrewAI via MCP

Follow these steps to integrate the JobScore MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from JobScore

Why Use CrewAI with the JobScore MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with JobScore through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

JobScore + CrewAI Use Cases

Practical scenarios where CrewAI combined with the JobScore MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries JobScore for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries JobScore, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain JobScore tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries JobScore against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

JobScore MCP Tools for CrewAI (10)

These 10 tools become available when you connect JobScore to CrewAI via MCP:

get_candidate

Returns contact history, resume highlights (if available), and current application status. Use this before an interview or when evaluating an applicant. Retrieves details for a specific candidate

get_job

Includes job descriptions, requirements, and hiring team identifiers. Use this to provide detailed information about a specific opening. Retrieves details for a specific job

get_me

Use this to verify connection status and identity. Gets current authenticated user info

list_candidates

Includes candidate names, current stage, and IDs. Essential for monitoring the talent pool and identifying new applications. Lists all candidates

list_departments

g., Engineering, Marketing) used to categorize jobs in JobScore. Useful for filtering hiring data by business unit. Lists all departments

list_hiring_teams

Useful for identifying recruiters and hiring managers associated with specific jobs. Lists all hiring teams

list_jobs

Returns job titles, IDs, and departments. Use this to identify active positions or find a job ID for candidate management. Lists all jobs in JobScore

list_locations

Useful for understanding the geographical scope of hiring efforts. Lists all office locations

list_sources

g., "LinkedIn", "Referral", "Job Board") from which candidates are originating. Essential for analyzing the effectiveness of hiring channels. Lists all candidate sources

list_users

Useful for identifying team members and their roles. Lists all users in the account

Example Prompts for JobScore in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with JobScore immediately.

"List all open jobs in JobScore."

"Show me the details for candidate ID '789'."

"Check the hiring team for the 'Software Engineer' job."

Troubleshooting JobScore MCP Server with CrewAI

Common issues when connecting JobScore to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

JobScore + CrewAI FAQ

Common questions about integrating JobScore MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.