How do I find my Flystack API Key?

Log in to your [**Flystack dashboard**](https://app.flystack.dev/), go to your account settings or API section, and generate a new token. Copy and paste it below.

Does it support real-time metrics?

Yes. The `get_cluster_metrics` tool retrieves the latest available CPU and memory usage metadata for your specified infrastructure cluster.

Can the agent list multiple deployments?

Yes. The `list_flystack_deployments` tool provides a comprehensive list of all active deployments in your account instantly.

Flystack MCP Server for CrewAI 5 tools — connect in under 2 minutes

Name: Flystack
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 5 Tools Framework

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

from crewai import Agent, Task, Crew

agent = Agent(
    role="Flystack Specialist",
    goal="Help users interact with Flystack effectively",
    backstory=(
        "You are an expert at leveraging Flystack 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 Flystack "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 5 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 Flystack MCP Server

Empower your AI agent to orchestrate your entire cloud infrastructure and deployment auditing workflow with Flystack, the comprehensive source for programmable infrastructure data. By connecting Flystack to your agent, you transform complex DevOps tasks into a natural conversation. Your agent can instantly retrieve active deployments, audit cluster health, and monitor performance metrics without you ever touching a cloud console. Whether you are conducting system audits or managing application scaling, your agent acts as a real-time infrastructure consultant, ensuring your data is always comprehensive and up-to-the-minute.

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

Deployment Auditing — Retrieve high-resolution details for all active deployments, including status, region, and creation metadata.
Cluster Oversight — Audit the health and configuration of your infrastructure clusters to maintain strict organizational control.
Performance Intelligence — Query real-time metrics including CPU and memory usage to understand the operational scale of your applications instantly.
Resource Discovery — Retrieve detailed metadata for specific deployment IDs to assist in deep-dive infrastructure classification.
Operational Monitoring — Check API status to ensure your infrastructure research workflow is always operational.

The Flystack MCP Server exposes 5 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 Flystack to CrewAI via MCP

Follow these steps to integrate the Flystack 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 5 tools from Flystack

Why Use CrewAI with the Flystack MCP Server

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

Flystack + CrewAI Use Cases

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

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

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

Flystack MCP Tools for CrewAI (5)

These 5 tools become available when you connect Flystack to CrewAI via MCP:

check_api_status

Check if the Flystack service is operational

get_cluster_metrics

Get real-time performance metrics for a specific cluster

get_deployment_details

Get full details for a specific deployment by ID

list_flystack_clusters

List all infrastructure clusters in your Flystack account

list_flystack_deployments

List all active deployments in your Flystack account

Example Prompts for Flystack in CrewAI

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

"List all active deployments using Flystack."

"What are the metrics for cluster ID 'cluster-123'?"

"Show details for deployment 'api-gateway'."

Troubleshooting Flystack MCP Server with CrewAI

Common issues when connecting Flystack 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.

Flystack + CrewAI FAQ

Common questions about integrating Flystack 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.