# Kubernetes Resource Request Calculator MCP for AI Agents MCP

> Kubernetes Resource Request Calculator helps you stop guessing your K8s pod sizes. It takes your actual usage metrics like p95 or p99 and turns them into accurate CPU and memory requests and limits. It also checks if your scaling ratios make sense and projects out how much total space your fleet will need.

## Overview
- **Category:** infrastructure
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_XwKoTMcUkhyOCkZdcYlfU4k00pRK7eRAzqyUhny3/mcp
- **Tags:** k8s, kubernetes, devops, resource-management, cloud-native

## Description

Setting up Kubernetes resources usually involves a lot of trial and error. You either over-provision and waste money on idle capacity, or you under-provision and watch your pods crash under load in the middle of the night. This MCP changes that by letting your AI client do the heavy math for you based on real usage data. Instead of guessing, you can feed in your observed usage percentiles and let the tool calculate the right specifications for your pods. It handles the tedious work of applying multipliers and checking your scaling ratios against industry standards. If you're trying to plan out a large deployment, it can even project your total cluster demand based on your replica counts. It's a much faster way to get production-ready configs without the manual spreadsheet work or the constant worry about OOM errors. You'll find this is a huge time-saver when you're managing complex environments where precision actually matters. It's one of the handy tools you'll find in the Vinkius catalog for getting your infra right. It takes the guesswork out of your resource planning so you can focus on shipping features instead of troubleshooting pod crashes.

## Tools

### estimate_cluster_demand
Projects total resource needs for a deployment based on pod specs and replica counts. It helps you plan your cluster capacity before you hit deploy.

### generate_resource_specification
Creates a full resource configuration using your actual usage history. It automates the math required to set accurate limits.

### validate_scaling_ratio
Checks if your limit-to-request ratio stays within safe operational boundaries. It prevents you from setting aggressive ratios that could cause instability.

## Prompt Examples

**Prompt:** 
```
Generate a resource spec using p95 CPU of 0.5, p95 memory of 512MB (536870912 bytes), and a multiplier of 1.5.
```

**Response:** 
```
| Metric | Request | Limit |
| :--- | :--- | :--- |
| **CPU** | 0.5 cores | 0.75 cores |
| **Memory** | 536,870,912 bytes | 805,306,368 bytes |

**QoS Class:** Burstable
```

**Prompt:** 
```
Is a scaling ratio of 2.0 considered safe?
```

**Response:** 
```
The ratio 2.0 is classified as being in the **Aggressive** zone. This means you're allowing for significant bursting, which is fine for some workloads but might lead to instability if your node resources are tight.
```

**Prompt:** 
```
If I have 10 replicas, each needing 0.2 CPU and 256MB memory, what is the total demand?
```

**Response:** 
```
**Total Demand Projection:**
*   **Total CPU Demand:** 2.0 cores
*   **Total Memory Demand:** 2,684,354,560 bytes
```

## Capabilities

### Create resource specs from usage history
Generate production-ready configurations based on your actual observed metrics.

### Project total cluster requirements
Calculate the total resource footprint for new deployments based on replica counts.

### Check scaling ratio safety
Verify if your limit-to-request ratios stay within recommended operational boundaries.

### Calculate CPU and memory limits
Automatically derive resource limits using your preferred multipliers and percentiles.

### Validate burst boundaries
Identify potential stability issues by checking your scaling ratios.

### Generate production-ready configurations
Get complete resource configurations ready for your K8s environment.

## Use Cases

### Sizing a new microservice
A developer needs to size a new microservice. They ask the agent to generate a resource spec using p95 CPU of 0.5 and a 1.5x multiplier.

### Verifying scaling ratios
An SRE wants to know if a 2.0 scaling ratio is safe for a high-traffic app. They ask the agent to validate the ratio.

### Planning a large rollout
A team is planning a 50-replica rollout. They ask the agent to project the total cluster demand for the entire fleet.

### Estimating monthly costs
A cloud architect needs to know the total memory footprint for a new environment to estimate monthly costs.

## Benefits

- Stop wasting money on over-provisioned pods by using `generate_resource_specification` to get precise limits based on real usage data.
- Prevent OOM kills by letting your agent calculate memory requests based on p95 usage metrics instead of manual guesses.
- Plan your infrastructure budget accurately with `estimate_cluster_demand` for fleet-wide planning and capacity forecasting.
- Avoid Aggressive scaling issues by using `validate_scaling_ratio` to check if your burst boundaries are safe.
- Save hours of manual spreadsheet work by automating the derivation of your pod specs directly from your metrics.
- Get production-ready configurations quickly so you can move from testing to deployment without extra math.

## How It Works

The bottom line is you get data-driven Kubernetes configs instead of manual guesswork.

1. Input your historical usage percentiles like p95 or p99 and your desired multiplier.
2. Ask your agent to generate a new resource specification or validate a specific scaling ratio.
3. Receive a production-ready configuration or a projected demand report for your fleet.

## Frequently Asked Questions

**How does the Kubernetes Resource Request Calculator help with my cloud bill?**
It helps you avoid over-provisioning by calculating the exact CPU and memory limits your pods actually need based on your usage data, ensuring you don't pay for idle resources.

**Can I use the Kubernetes Resource Request Calculator to prevent OOM kills?**
Yes, by using your p95 or p99 memory usage metrics, the tool calculates a request and limit that provides a realistic buffer for your workload.

**How do I know if my K8s scaling ratios are safe?**
You can use the tool to check your limit-to-request ratios. It will tell you if your current configuration is in a safe zone or an Aggressive zone.

**Can this tool help me plan my cluster capacity?**
Yes, it can project the total resource demand for an entire deployment based on your pod specifications and the number of replicas you plan to run.

**What metrics do I need to provide to the Kubernetes Resource Request Calculator?**
You just need to provide your observed usage percentiles, such as p50, p95, or p99, along with a multiplier for how much overhead you want to include.

**Does the Kubernetes Resource Request Calculator create my YAML files?**
It generates the full resource configuration for you, which you can then copy directly into your Kubernetes manifest files.

**How does the tool calculate CPU and memory requests?**
The `generate_resource_specification` tool looks up the value in your provided metrics (p50, p95, or p99) that matches your chosen strategy percentile and sets that as the request.

**What is a 'Guaranteed' QoS class?**
A pod is in the Guaranteed class if both its CPU request equals its limit and its memory request equals its limit.

**Can I use this to plan for large-scale deployments?**
Yes, you can use `estimate_cluster_demand` to project the total CPU and memory footprint required for any number of replicas.