How do I find the shortcode for a specific job?

Use the `list_jobs` tool. It returns a list of all your openings, each with its unique shortcode required for more detailed queries or actions.

Can I add a new candidate directly to a job via AI?

Yes! Use the `create_candidate` action. Provide the job shortcode along with the candidate's name and email to register them in your Workable pipeline.

Is it possible to see the recruiter assigned to an account?

Absolutely. Run the `list_account_members` query to retrieve the directory of all users and recruiters in your instance, including their roles.

INSTANT PLUG AND PLAY

Workable MCP Server for CrewAIGive CrewAI instant access to 7 tools to Create Candidate, Get Candidate Profile, Get Job Details, and more

Name: Workable
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 7 Tools Framework

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

Use with Your AI Agent

Ask AI about this App Connector for CrewAI

Open in ChatGPT Open in Claude Open in Perplexity

The Workable app connector for CrewAI is a standout in the Productivity category — giving your AI agent 7 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Workable Specialist",
    goal="Help users interact with Workable effectively",
    backstory=(
        "You are an expert at leveraging Workable 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 Workable "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 7 available tools "
        "and what they can do."
    ),
)

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

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* 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 Workable MCP Server

Connect your Workable recruiting account to any AI agent and simplify how you manage your hiring pipelines, track candidates, and coordinate with your team through natural conversation.

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

What you can do

Job Management — List all active and archived job openings and retrieve detailed job descriptions and requirements.
Candidate Tracking — List and inspect candidates across all jobs, and drill down into specific profiles for experience and status.
Direct Sourcing — Programmatically register new candidates to specific job openings to accelerate your hiring process.
Team Coordination — List account members and recruiters to understand your hiring team structure.
Ecosystem Overview — List linked accounts and verify your Workable instance configuration via AI.

The Workable MCP Server exposes 7 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.

All 7 Workable tools available for CrewAI

When CrewAI connects to Workable through Vinkius, your AI agent gets direct access to every tool listed below — spanning applicant-tracking, hiring-workflow, candidate-screening, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

create_candidate

get_candidate_profile

Get details for a specific candidate

get_job_details

Get details for a specific job

list_account_members

List hiring team members

list_all_candidates

List candidates across all jobs

list_jobs

List active job openings

list_linked_accounts

List connected accounts

Connect Workable to CrewAI via MCP

Follow these steps to wire Workable into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

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 7 tools from Workable

Why Use CrewAI with the Workable MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Workable 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

Workable + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Workable 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 Workable, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Workable 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 Workable against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Workable in CrewAI

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

"List all active job openings in our Workable account."

"Show me the details for the candidate 'John Smith'."

"Add 'Jane Doe' (jane.doe@example.com) as a candidate for the job 'ENG-101'."

Troubleshooting Workable MCP Server with CrewAI

Common issues when connecting Workable 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.

Workable + CrewAI FAQ

Common questions about integrating Workable 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.