Where do I find my Kolide API Token?

Log in to the Kolide dashboard, navigate to **Settings** in the bottom left, and select the **API** tab to generate a token.

Can I see hardware details of a device?

Yes, the `get_device_details` tool returns hardware specifications along with security data.

Does this support multi-tenant accounts?

The API key is typically scoped to a specific organization. Ensure you are using the token for the desired fleet.

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

Name: Kolide
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Kolide through Vinkius, pass the Edge URL in the `mcps` parameter and every Kolide 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

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

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

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

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 Kolide MCP Server

Connect your AI agent to Kolide to get full visibility into your organization's fleet security and device health.

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

Key Features

Fleet Inventory — List all managed devices and their high-level security status
Issue Tracking — Monitor active security vulnerabilities and misconfigurations across your fleet
People & Ownership — See which users are associated with which devices and their individual compliance state
Security Checks — Audit available security checks and dive into specific failure conditions
Audit Logs — Access a chronological history of administrative and security events

How to setup

1. Subscribe to this server
2. Log in to Kolide, go to Settings > API, and generate a Bearer Token
3. Enter your token in the configuration
4. Start auditing your fleet via natural language

The Kolide 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 Kolide to CrewAI via MCP

Follow these steps to integrate the Kolide 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 Kolide

Why Use CrewAI with the Kolide MCP Server

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

Kolide + CrewAI Use Cases

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

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

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

Kolide MCP Tools for CrewAI (10)

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

get_check_details

Get details for a specific check

get_device_details

Get details for a specific device

get_issue_details

Get details for a specific security issue

get_kolide_fleet_stats

g., total devices, online status, issue count). Get high-level fleet statistics

get_person_details

Get details for a specific person

list_kolide_audit_logs

List fleet audit logs

list_kolide_checks

List all available security checks

list_kolide_devices

Use this to audit fleet security posture and identify individual device IDs. List all devices in the fleet

list_kolide_issues

List security issues across the fleet

list_kolide_people

List people/users managed in Kolide

Example Prompts for Kolide in CrewAI

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

"List all devices currently online in Kolide"

"What are the most common security issues in my fleet?"

"Show fleet statistics for today"

Troubleshooting Kolide MCP Server with CrewAI

Common issues when connecting Kolide 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.

Kolide + CrewAI FAQ

Common questions about integrating Kolide 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.