Bring Kubernetes
to LlamaIndex
Learn how to connect OpenCost (K8s Cost) to LlamaIndex and start using 6 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the OpenCost (K8s Cost) MCP Server?
Connect your OpenCost instance to any AI agent to gain real-time visibility into your Kubernetes spending and infrastructure efficiency through natural language.
What you can do
- Workload Allocation — Query costs and resources allocated to clusters, nodes, namespaces, controllers, and pods using
get_allocation. - Asset Inspection — Retrieve backing cost data for physical infrastructure like Nodes, Disks, and Load Balancers via
get_assets. - Cloud Billing Integration — Access AWS CUR, Azure Export, and GCP Billing data directly with
get_cloud_costto reconcile K8s costs with provider bills. - Third-Party Costs — Track external service expenses (e.g., Datadog, MongoDB Atlas) using custom cost timeseries and total summary tools.
- Granular Filtering — Aggregate data by labels, annotations, or service levels to understand exactly where your budget is going.
How it works
- Subscribe to this server
- Enter your OpenCost API Base URL
- Start auditing your cloud spend from Claude, Cursor, or any MCP client
Who is this for?
- DevOps & Platform Engineers — Identify expensive namespaces or orphaned resources without manual dashboard diving.
- FinOps Teams — Reconcile internal Kubernetes allocations with external cloud provider billing reports instantly.
- Engineering Managers — Get quick summaries of project-based costs to stay within budget during development cycles.
Built-in capabilities (6)
Query costs and resources allocated to Kubernetes workloads
Retrieve backing cost data broken down by individual assets
Retrieve cloud cost data directly from cloud provider billing reports
g., Datadog, MongoDB Atlas). Get samples of third-party service costs over time steps
Get summary of third-party costs over a window
Change OpenCost log level at runtime
Why LlamaIndex?
LlamaIndex agents combine OpenCost (K8s Cost) tool responses with indexed documents for comprehensive, grounded answers. Connect 6 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
- —
Data-first architecture: LlamaIndex agents combine OpenCost (K8s Cost) tool responses with indexed documents for comprehensive, grounded answers
- —
Query pipeline framework lets you chain OpenCost (K8s Cost) tool calls with transformations, filters, and re-rankers in a typed pipeline
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Multi-source reasoning: agents can query OpenCost (K8s Cost), a vector store, and a SQL database in a single turn and synthesize results
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Observability integrations show exactly what OpenCost (K8s Cost) tools were called, what data was returned, and how it influenced the final answer
OpenCost (K8s Cost) in LlamaIndex
OpenCost (K8s Cost) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect OpenCost (K8s Cost) to LlamaIndex through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for OpenCost (K8s Cost) in LlamaIndex
The OpenCost (K8s Cost) 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. All 6 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in LlamaIndex only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
OpenCost (K8s Cost) for LlamaIndex
Every tool call from LlamaIndex to the OpenCost (K8s Cost) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I see costs grouped by a specific Kubernetes namespace?
Yes. Use the get_allocation tool and set the aggregate parameter to 'namespace'. You can also specify a window like '7d' to see trends over the last week.
Does this server support viewing external cloud provider billing?
Absolutely. The get_cloud_cost tool retrieves data directly from cloud provider billing reports (AWS CUR, Azure Export, GCP Billing) to give you a complete financial picture.
Can I track costs for non-Kubernetes services like Datadog?
Yes, if configured in your OpenCost instance, you can use get_custom_cost_total or get_custom_cost_timeseries to query costs for third-party SaaS and infrastructure services.
How does LlamaIndex connect to MCP servers?
Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
Can I combine MCP tools with vector stores?
Yes. LlamaIndex agents can query OpenCost (K8s Cost) tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
Does LlamaIndex support async MCP calls?
Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.
BasicMCPClient not found
Install: pip install llama-index-tools-mcp
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