How do I get a Crelate API Key?

Log in to Crelate, navigate to **Settings > API**, and you will find your API Key there. You may need to enable API access first.

Can the agent update candidate statuses?

This integration currently focuses on listing and retrieving candidate profiles and notes. Updating statuses would require additional write permissions and specific tool configuration.

Does Crelate support custom fields?

Yes, Crelate's API provides access to custom fields. The agent can retrieve these fields as part of the full candidate or job profile.

Crelate Talent CRM MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Crelate Talent CRM
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Crelate Talent CRM Specialist",
    goal="Help users interact with Crelate Talent CRM effectively",
    backstory=(
        "You are an expert at leveraging Crelate Talent CRM 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 Crelate Talent CRM "
        "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)

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About Crelate Talent CRM MCP Server

Integrate Crelate, the specialized recruiting CRM and applicant tracking system (ATS), directly into your AI workflow. Manage your talent pipeline, monitor job orders, and track candidate activities using natural language.

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

What you can do

Candidate Management — List, search, and retrieve full profiles for candidates and contacts.
Job Tracking — Monitor open and past job opportunities and their current status.
Activity Logging — Review recent recruiting activities including calls, emails, and internal notes.
Client Relationship — Manage company records and associated client data seamlessly.

The Crelate Talent CRM 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 Crelate Talent CRM to CrewAI via MCP

Follow these steps to integrate the Crelate Talent CRM 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 Crelate Talent CRM

Why Use CrewAI with the Crelate Talent CRM MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Crelate Talent CRM 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 the 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

Crelate Talent CRM + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Crelate Talent CRM MCP Server delivers measurable value.

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

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

Crelate Talent CRM MCP Tools for CrewAI (10)

These 10 tools become available when you connect Crelate Talent CRM to CrewAI via MCP:

create_contact

Add a new candidate or contact to the database

get_contact_details

Get detailed profile for a specific candidate or contact

get_contact_notes

List internal notes for a specific contact

get_job_details

Get detailed information for a specific job order

list_companies

List all companies and client records

list_contacts

List all candidate and contact records in Crelate

list_crelate_users

List internal recruiters and team members

list_jobs

List open and past job opportunities

list_recent_activities

List recent recruiting activities (calls, emails, notes)

search_contacts_by_name

Search for contacts by name keyword

Example Prompts for Crelate Talent CRM in CrewAI

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

"List all candidates who applied for the 'Senior Developer' job."

"Show me the recent activity for candidate 'Sarah Jones'."

"List all open jobs in the 'Engineering' department."

Troubleshooting Crelate Talent CRM MCP Server with CrewAI

Common issues when connecting Crelate Talent CRM 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

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

Crelate Talent CRM + CrewAI FAQ

Common questions about integrating Crelate Talent CRM 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.