OpenCost (K8s Cost) MCP. Reconcile complex cloud billing data instantly.
OpenCost (K8s Cost) connects your AI client directly to your Kubernetes billing data. Query cost allocations for specific workloads, check costs tied to physical assets like Nodes or Disks, and reconcile complex cloud provider bills (AWS CUR, Azure Export, GCP). It gives you natural language visibility into exactly where your cluster spending goes.
Give Claude and any AI agent real-world access
Query costs based on Kubernetes workloads across clusters, nodes, and namespaces.
Retrieve cost data associated with underlying infrastructure assets like disks or load balancers.
Match internal Kubernetes spending against official bills from major cloud providers (AWS, Azure, GCP).
Get time-series data and summaries for external tools like Datadog or MongoDB Atlas.
Aggregate spending by labels, annotations, or defined service levels to pinpoint budget usage.
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What AI agents can do with OpenCost (K8s Cost) with 6 Tools
These tools allow your agent to query specific cost data points, retrieve asset details, pull cloud bills, and summarize third-party expenses based on the OpenCost API.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using OpenCost (K8s Cost) MCPGet Allocation
Queries the cost and resource usage allocated to specific Kubernetes workloads.
Get Assets
Retrieves detailed backing cost information for individual infrastructure assets.
Get Cloud Cost
Pulls raw cloud spending data directly from official provider billing reports (AWS...
Get Custom Cost Timeseries
Provides time-series samples of costs for third-party services like Datadog or...
Get Custom Cost Total
Generates a total summary calculation for third-party service expenses over a...
Set Log Level
Changes the internal logging verbosity of the OpenCost system at runtime.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with OpenCost (K8s Cost), then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
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The Struggle of Merging Cloud Bills
Today, figuring out cloud spend means a nightmare. You're staring at three separate dashboards: the AWS cost report, the Azure export file, and your internal K8s usage dashboard. Then you have to copy-paste data from one into a spreadsheet, trying to find matching resource IDs and dates so you can even start reconciling which bill paid for what actual workload.
With this MCP, that entire process disappears. You talk to your agent like talking to a teammate, asking it to compare the cost allocation of your 'production' namespace against the official cloud provider billing report. It handles the cross-referencing instantly and gives you the answer—no spreadsheets required.
Get Full Visibility with OpenCost (K8s Cost) MCP
You no longer have to manually query costs for specific assets or run separate reports for every external tool. The agent can consolidate everything: it checks the backing cost data using `get_assets`, pulls billing details via `get_cloud_cost`, and sums up third-party overhead with a single prompt.
What's different is that you get deep, actionable insights without ever leaving your conversational workflow. It turns complex financial auditing into simple conversation.
What OpenCost (K8s Cost) MCP does for your AI
OpenCost lets you talk to your infrastructure budget. Instead of diving through confusing dashboards and merging multiple billing spreadsheets, you just ask your AI agent questions about your Kubernetes costs in plain English. You can find out which specific namespace or controller is chewing up the most resources, or see how much compute power on a physical Node cost this month.
It pulls together data from core cloud provider bills—like AWS CUR or Azure exports—and cross-references it with internal workload allocations. This means you don't just get a total number; you get visibility into exactly why that number is what it is, helping your team maintain budget discipline while developing and running services.
When you connect this MCP via the Vinkius catalog, your agent gains access to all these cost metrics in one place.
019e38cd-b00c-706a-aefe-9f756dec0209 How to set up OpenCost (K8s Cost) MCP
The bottom line is you get an immediate, accurate report on infrastructure costs without ever leaving your chat window or IDE.
Subscribe to this MCP and enter your OpenCost API Base URL.
Your AI client connects the cost data source to your agent's context.
You ask a natural language question, and the system returns precise spending figures linked to specific resources.
Who uses OpenCost (K8s Cost) MCP
DevOps and FinOps Engineers. You're the one who gets tired of spending weekends clicking through disparate cloud dashboards just to answer 'Where did this feature get so expensive?'
Uses the MCP to quickly identify namespaces or resources that have become unexpectedly costly, preventing budget overruns before they happen.
Connects cloud billing reports with internal K8s usage data to prove cost attribution and reconcile discrepancies between systems.
Gets a summary of project-based spending trends, providing quick financial oversight during development cycles without needing deep technical knowledge.
Benefits of connecting OpenCost (K8s Cost) MCP
Identify spending culprits: Instead of manually checking ten namespaces, you can ask the agent to check allocation for all clusters and pinpoint exactly which controllers or pods are driving up costs using get_allocation.
Connect the dots: You don't have to merge separate AWS CUR files with your internal reports. The MCP lets you use get_cloud_cost to pull provider data and compare it directly against K8s usage metrics in one query.
Track hardware costs: Need to know what underlying infrastructure is costing? Use get_assets to retrieve cost data for physical components like Nodes or Disks, giving a full picture of your spend.
Monitor external tools: Beyond the cloud provider, you can track third-party services. Use get_custom_cost_timeseries and get_custom_cost_total to summarize costs from Datadog or MongoDB Atlas over time.
Pinpoint leakage: The MCP allows aggregation by labels and annotations. This lets your agent filter out the noise and tell you precisely where a specific project's budget is going.
OpenCost (K8s Cost) MCP use cases
Why did our staging environment suddenly spike in cost?
The Engineering Manager asks the agent to run get_allocation for the last quarter. The agent responds, detailing that a new logging controller deployed to the 'staging' namespace accounted for 40% of the unexpected increase, allowing them to immediately scale it back.
We need to compare our internal metrics against the official AWS bill.
The FinOps Analyst uses get_cloud_cost to retrieve the latest AWS CUR data. The agent then compares this raw provider data with the resource totals pulled via get_allocation, instantly flagging a 15% mismatch in EBS volume costs that needs review.
How much did our development team spend on monitoring tools last month?
The DevOps Engineer prompts the agent to get a total summary using get_custom_cost_total for Datadog and MongoDB Atlas. The result provides a clear, single figure showing the full cost of observability across all projects.
I need to know the compute cost for our primary nodes right now.
The user asks about backing assets today. The agent uses get_assets and reports that the 12 m5.large cluster nodes are incurring $45.20 in compute costs, including associated EBS volumes.
OpenCost (K8s Cost) MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Treating billing data like general knowledge
Asking the AI agent generally, 'What is our cloud spending?' This results in vague answers because the system doesn't know which bill or resource you mean.
Be specific and direct. Instead of a broad question, ask: 'Using get_cloud_cost, what was the total cost for EBS volumes last month?'. This forces the agent to use the correct tool.
Ignoring workload boundaries
Just seeing a massive lump sum of cost and not knowing which team or service caused it.
Use get_allocation combined with label filtering. Ask: 'Show me the allocation for all services labeled 'project-alpha' last week.' This immediately isolates project spending.
Forgetting third-party costs
Only looking at AWS/Azure bills and completely missing the cost of observability tools like Datadog.
Always check external services. Use get_custom_cost_total to ensure your summary includes all necessary monitoring and SaaS expenses.
When to use OpenCost (K8s Cost) MCP
Use this MCP if your primary job involves reconciling multiple, complex cost inputs: Kubernetes usage data, raw cloud provider bills (AWS CUR, etc.), AND third-party service invoices. You need a single source of truth to answer 'Why is the bill what it is?'
Don't use it if you only need basic billing reports or simple resource counts. If all you need is a list of nodes and their status without cost attached, a general cloud provider API might suffice. Similarly, if your costs are already perfectly siloed by one single system, this MCP offers overkill. But if your money lives in the gap between your K8s manifests and your actual invoices, this is exactly what you need.
Frequently asked questions about OpenCost (K8s Cost) MCP
How does OpenCost (K8s Cost) MCP handle multiple cloud providers? +
The MCP uses the get_cloud_cost tool to connect directly to various provider billing reports, including AWS CUR, Azure Export, and GCP Billing data. This means you can reconcile costs across different clouds from one place.
Can OpenCost (K8s Cost) MCP tell me which service is the most expensive? +
Yes. You can use get_allocation to query costs and resources allocated to specific namespaces, pods, or controllers to pinpoint your biggest spending areas.
What if I need cost data for services like Datadog? +
The MCP supports this via third-party tools. You use get_custom_cost_timeseries and get_custom_cost_total to track external service expenses over time or get a summary total.
Is OpenCost (K8s Cost) MCP only for AWS? +
No. It is designed to be cloud-agnostic, pulling data from multiple sources including Azure and GCP in addition to AWS billing reports.
How do I check the cost of a physical node using OpenCost (K8s Cost) MCP? +
Use the get_assets tool. This retrieves backing cost data broken down by individual assets, giving you visibility into nodes, disks, and load balancers.