How do I get a Namely API Token?

You can generate a Personal Access Token in your Namely account under API > Personal Access Tokens. Ensure your user has the appropriate permissions to view the data you want to retrieve.

Can I see salary information through this server?

This depends on the permissions of the user who generated the API token. If your Namely user can see salary data, the `get_profile` and `list_jobs` tools will return that information.

What is the Company Slug?

The slug is the unique part of your Namely URL. For example, if you log in at 'acme.namely.com', your slug is 'acme'.

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

Name: Namely
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Namely through Vinkius, pass the Edge URL in the `mcps` parameter and every Namely 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="Namely Specialist",
    goal="Help users interact with Namely effectively",
    backstory=(
        "You are an expert at leveraging Namely 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 Namely "
        "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

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IAMAccess control

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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 Namely MCP Server

Connect your Namely HRIS account to your AI agent and take full control of your organization's employee data and structures through natural conversation.

When paired with CrewAI, Namely becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Namely 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

Employee Directory — List all employee profiles and get detailed information including contact info and roles.
Job & Salary Info — Access a complete list of job titles and salary structures defined in your organization.
Org Structure — View all groups, departments, and teams to understand your organizational hierarchy.
HR Timeline — Monitor organization events like birthdays and work anniversaries.
Custom Fields & Reports — List available reports and custom data fields defined for your profiles.
Company Feed — Access recent company-wide announcements from the Namely home feed.

The Namely 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 Namely to CrewAI via MCP

Follow these steps to integrate the Namely 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 Namely

Why Use CrewAI with the Namely MCP Server

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

Namely + CrewAI Use Cases

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

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

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

Namely MCP Tools for CrewAI (10)

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

get_profile

Get specific employee details

get_team

Get team details

list_announcements

List company announcements

list_events

g., birthdays, work anniversaries) from the organization timeline. List HR events

list_fields

List custom employee fields

list_groups

g., departments, offices) in your organization. List organization groups

list_jobs

List job titles and info

list_profiles

List employee profiles

list_reports

List HR reports

list_teams

List organization teams

Example Prompts for Namely in CrewAI

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

"List all employees in the 'Engineering' department."

"What company announcements were posted recently?"

"Show me upcoming birthdays in the organization."

Troubleshooting Namely MCP Server with CrewAI

Common issues when connecting Namely 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.

Namely + CrewAI FAQ

Common questions about integrating Namely 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.