How to Use the Workable MCP in CrewAI

Q: How do I get job details using Workable and CrewAI?

You define a role that uses the getjobdetails tool. The crew executes this step, providing the data to other specialized agents for analysis or comparison.

Q: What is the best way to track candidates with Workable and CrewAI?

Assign a dedicated agent role that uses listallcandidates. This allows an entire 'crew' to monitor, analyze, and report on every applicant automatically.

Q: Can I see team structure using Workable and CrewAI?

Yes. A Monitoring Agent can run the listaccountmembers tool. This information is then passed to a Moderator Agent that summarizes who's available for hiring decisions.

Q: What kind of accounts info can I pull with Workable and CrewAI?

The crew uses the listlinkedaccounts tool. This allows an agent to quickly gather context from connected systems, making its analysis much richer.

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Connect Workable MCP to CrewAI

Create your Vinkius account to connect Workable 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 Workable with CrewAI

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Run a full audit of all job openings.

Set up a Monitor Agent to watch for open roles. It can repeatedly call `list_jobs` and compare that list against internal records, flagging any discrepancies automatically. The crew doesn't just report; it identifies gaps in your staffing pipeline without human intervention.

Research a candidate’s full history.

A specialized Researcher Agent can use `get_candidate_profile` to pull detailed data. A separate Analyzer Agent then reviews that profile, comparing the skills against job requirements from `get_job_details`. This sequential execution of roles simulates human expert review.

Maintain a centralized list of all talent.

You can assign an Action Agent to run `list_all_candidates`. This agent aggregates the data, and another agent structures it into a clean report that's ready for decision-makers. The system manages this shared memory across multiple specialized roles.

Setup guide

Set up Workable 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 Workable tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Workable 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 Workable MCP in CrewAI

You define a role that uses the `get_job_details` tool. The crew executes this step, providing the data to other specialized agents for analysis or comparison.

Assign a dedicated agent role that uses `list_all_candidates`. This allows an entire 'crew' to monitor, analyze, and report on every applicant automatically.

Yes. A Monitoring Agent can run the `list_account_members` tool. This information is then passed to a Moderator Agent that summarizes who's available for hiring decisions.

The crew uses the `list_linked_accounts` tool. This allows an agent to quickly gather context from connected systems, making its analysis much richer.

This Workable MCP Server handles structured recruitment and talent pipeline data, including job openings and applicant profiles. CrewAI allows you to build complex operations around that data.

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