How to Use the Jaicob MCP in CrewAI

Q: How do I limit Jaicob tools for specific agents in CrewAI?

Use the toolfilter parameter in your agent configuration. You can restrict which agents have access to write-heavy tools like the candidate creation endpoint.

Deploy autonomous recruitment teams using Jaicob and CrewAI for end-to-end hiring.

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Connect Jaicob MCP to CrewAI

Create your Vinkius account to connect Jaicob 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 Jaicob with CrewAI

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Perplexity

Specialized agent teams for recruitment

Assign one agent to `list_vacancies` while another handles `list_applications` analysis. CrewAI coordinates these agents so they share a coherent view of your hiring needs. It functions like a real office. One agent finds the data, the other makes the decision, and the process moves forward without you needing to manage the details.

Autonomous pipeline monitoring

Let your crew monitor `list_recruitment_leads` for new entries. When a match appears, the agent can draft a response based on the client's requirements. It removes the lag between lead generation and follow-up. Your autonomous team stays on top of the queue 24/7.

Sequential hiring orchestration

Chain `list_candidates` and `create_candidate` to build a self-organizing talent database. The crew checks for duplicates before adding new entries to your system. This keeps your data clean and actionable. Your agents handle the messy work of parsing and validating records so you can focus on interviewing.

Setup guide

Set up Jaicob 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 Jaicob tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Use the tool_filter parameter in your agent configuration. You can restrict which agents have access to write-heavy tools like the candidate creation endpoint.

The server provides the data, and CrewAI handles the shared memory state. Your agents will be able to reference previous tool outputs during the conversation.

Yes, you can nest the MCP Server within your hierarchical manager agent. The manager can then delegate tool usage to sub-agents as needed.

Enable logging on your MCP transport. You will see every tool call and response in your terminal, which makes tracking down logic errors much simpler.

The server only processes the text you request. We never cache resume files or candidate documents, ensuring data privacy across your autonomous crew.

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