We're launching the DoiT Cloud Intelligence™ remote MCP server, making it easy for you to access your real-time cloud cost and usage data through AI assistants like Claude, ChatGPT, and Cursor. 

Anyone can now ask plain-language questions about their cloud usage, connect it to business context  — like “Can you connect our recent database cost spike to any Jira tickets?” (see example below 👇 ) — and get instant, context-rich answers.

What's different with remote access?

Our remote MCP server eliminates the technical setup that our previously-launched local version required, making conversational cloud cost analysis accessible to finance teams, executives, and other business stakeholders. 

Here's what makes the remote approach different:

• Easy setup: Connect AI tools to your cost data without any technical setup—no Node.js installations or configuration troubleshooting that come with locally-hosted MCP servers.
• Real-time data access: Our remote server maintains live connections to your DoiT Cloud Intelligence data, ensuring everyone accesses the same, current information without having to manually update to the latest version.

Democratizing cloud intelligence beyond technical teams

This remote approach brings cloud intelligence directly to non-technical roles across your company. 

And for even richer insights, you can connect with MCP servers from other tools you use (ex. Jira, Slack, GitHub) to understand the full business context behind your cost data:

Finance teams can analyze budget variance and forecast accuracy during monthly reviews.

For example: You can use Claude to get the full business context behind a 30% budget overrun highlighted in Budgets by connecting it to an approved GPU increase documented in Jira.

Product managers can evaluate feature profitability and unit economics for roadmap decisions.

For example: When analyzing a new feature costing $350/day (15% over budget), you can correlate it with performance issues listed in Jira tasks and Zendesk tickets and enable more-informed cost/performance trade-off conversations.

Operations teams can correlate infrastructure changes with spending pattern.

When you ask Claude about a 25% EC2 cost spike highlighted by Anomaly Detection, you can determine whether or not it was a planned scaling event by connecting it to a recent deployment in Jira and engineer discussions in Slack.

Ready to understand the full business story behind your cloud costs?  Connect to DoiT’s remote MCP server and start asking questions.