How do I get a DoiT API Key?

Log in to your DoiT Console, navigate to **Settings > API**, and you can generate or retrieve your unique API Key from there. Ensure your user has the necessary administrative permissions.

Which cloud platforms are supported?

DoiT supports major cloud providers including Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure.

Can the agent show me real-time spending alerts?

Yes, you can use the list_cost_anomalies or list_critical_cost_spikes tools to identify unexpected spending increases across your infrastructure instantly.

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

Name: DoiT
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

Integrate DoiT, the leading cloud cost management and optimization platform, directly into your AI workflow. Manage your multi-cloud assets across AWS, Google Cloud, and Microsoft Azure, monitor real-time cost anomalies and budgets, and track your cloud spending using natural language.

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

Cloud Oversight — List and retrieve detailed configuration and cost data for all your cloud assets and connected accounts.
Anomaly Intelligence — Monitor real-time cost anomalies and unexpected spending spikes across your cloud infrastructure.
Budget Monitoring — Track cloud spending budgets, threshold limits, and current consumption percentages.
Cost Auditing — Retrieve high-level summaries of total cloud expenditure and identify high-severity cost spikes instantly.

The DoiT 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 DoiT to CrewAI via MCP

Follow these steps to integrate the DoiT 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 DoiT

Why Use CrewAI with the DoiT MCP Server

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

DoiT + CrewAI Use Cases

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

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

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

DoiT MCP Tools for CrewAI (10)

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

get_asset_details

Get detailed configuration and cost data for a specific cloud asset

get_billing_cost_summary

Retrieve a high-level summary of total cloud spending across all platforms

get_doit_account_metadata

Retrieve metadata for the current DoiT organization

list_cloud_assets

List all cloud assets (AWS, GCP, Azure) managed by DoiT

list_connected_cloud_accounts

List all connected AWS, GCP, or Azure accounts

list_cost_anomalies

List all detected cloud cost anomalies and unexpected spending spikes

list_cost_budgets

List all cloud spending budgets configured in DoiT

list_critical_cost_spikes

Identify high-severity cost anomalies that require immediate attention

list_exceeded_cost_budgets

Identify budgets that have exceeded their configured spending limits

search_cloud_assets

Search for cloud assets using a name keyword

Example Prompts for DoiT in CrewAI

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

"Show me our total cloud cost summary."

"Are there any critical cost anomalies right now?"

"List all budgets that have exceeded 100% consumption."

Troubleshooting DoiT MCP Server with CrewAI

Common issues when connecting DoiT 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.

DoiT + CrewAI FAQ

Common questions about integrating DoiT 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.