# WebSocket Capacity Planner MCP for AI Agents MCP

> WebSocket Capacity Planner helps you figure out how many nodes you need for your real-time apps. It calculates max connections based on RAM, figures out fleet size for global scale, and predicts network load from broadcasts or heartbeats. No more guessing at your infrastructure costs or hitting limits unexpectedly.

## Overview
- **Category:** infrastructure
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/undefined/mcp
- **Tags:** websocket, scaling, devops, network-engineering, performance

## Description

WebSocket Capacity Planner provides a specialized engine for planning your infrastructure. It allows your agent to calculate the maximum concurrent connections based on memory constraints, determine necessary fleet size, estimate network egress load, and quantify heartbeat bandwidth overhead. Planning for real-time communication is a headache because you're always balancing memory limits against user experience. If you're building a chat app or a live gaming platform, you need to know exactly when your current fleet will buckle. This MCP takes the guesswork out of the math. Instead of running manual spreadsheets or doing back of the envelope calculations that might be off by 50 percent, you can just ask your agent to run the numbers for you. You can get a hard count of how many concurrent users a single node can host before it runs out of memory, or see how much extra bandwidth your heartbeat pings are actually eating up. It's about getting a clear picture of your network egress before you actually launch. Because Vinkius makes it easy to plug this into your existing workflow, you can move from a vague idea of needing more hardware to a specific procurement list in seconds. It's about knowing your limits before you hit them. You can stop worrying about sudden traffic spikes crashing your production environment and start building with confidence.

## Tools

### calculate_bandwidth_overhead
Tells you exactly how much data your heartbeat pings are consuming. This helps you plan for steady-state network costs.

### calculate_required_servers
Gives you the total number of instances needed to hit a specific user target. It handles the math for scaling your fleet globally.

### estimate_broadcast_load
Predicts the network egress load when sending messages to multiple subscribers. It's essential for understanding fan-out costs.

### estimate_max_connections
Determines the maximum concurrent users a single node can host based on your RAM. It prevents your hardware from crashing due to memory exhaustion.

## Prompt Examples

**Prompt:** 
```
I have 16GB of RAM and each user takes 50KB. How many connections can I host?
```

**Response:** 
```
### Capacity Analysis
Based on your hardware specs, here is the breakdown:

*   **Total Available Memory:** 16,384,000 KB
*   **Memory Footprint per User:** 50 KB
*   **Max Concurrent Connections:** **327,680**

This assumes a steady state where each connection maintains a consistent memory footprint. You should leave a buffer for OS overhead and other processes.
```

**Prompt:** 
```
I need to support 1 million users. If each node handles 100k, how many do I need?
```

**Response:** 
```
### Fleet Requirement
To support your target audience, here is the required scale:

| Metric | Value |
| :--- | :--- |
| **Target Users** | 1,000,000 |
| **Capacity per Node** | 100,000 |
| **Total Nodes Needed** | **10** |

I recommend deploying a minimum of 10 instances to meet your target.
```

**Prompt:** 
```
What's the broadcast load for 100 messages/sec with 500 subscribers per channel?
```

**Response:** 
```
### Network Egress Estimate
For your broadcast configuration, the load is as follows:

*   **Messages per Second:** 100
*   **Fan-out Multiplier:** 500x
*   **Total Egress Load:** **50,000 messages per second**

You'll need to ensure your network backbone can handle this sustained throughput for the target channels.
```

## Capabilities

### Calculate max connections per node
Determines the maximum number of concurrent users a single instance can host based on your RAM.

### Determine total fleet size
Calculates the number of instances needed to hit a specific global user target.

### Predict broadcast network load
Estimates the network egress load generated by message broadcasting across channels.

### Measure heartbeat bandwidth overhead
Quantifies the bandwidth consumed strictly by heartbeat ping and pong traffic.

## Use Cases

### Scaling a chat app
A dev wants to support 1 million users and asks the agent to use calculate_required_servers to find the fleet size for a global rollout.

### Cost optimization
An engineer wants to see if they can squeeze more users onto 16GB RAM nodes and uses estimate_max_connections to find the max connection count.

### Broadcast planning
A gaming company needs to know the egress load for a 500-subscriber channel and uses estimate_broadcast_load to get a specific message-per-second count.

### Network auditing
A team wants to know if their pings are too heavy and uses calculate_bandwidth_overhead to measure the specific bandwidth overhead.

## Benefits

- Stop over-provisioning expensive hardware by using estimate_max_connections to find the exact limits of your current nodes.
- Get a clear picture of your global scale requirements with calculate_required_servers so you know exactly how many instances to buy.
- Avoid unexpected egress spikes by using estimate_broadcast_load to map out your message fan-out costs before launch.
- Fine-tune your heartbeat settings with calculate_bandwidth_overhead to keep your steady-state network costs as low as possible.
- Move from best guess to data-backed infrastructure planning by letting your agent handle all the complex math.

## How It Works

The bottom line is you get a data-backed infrastructure roadmap instead of a best guess.

1. Input your current hardware specs and per-connection memory footprint.
2. Tell the agent your target user count and expected message frequency.
3. Get a detailed breakdown of required instance counts and network overhead.

## Frequently Asked Questions

**What does the WebSocket Capacity Planner do?**
It helps you calculate exactly how many concurrent users your hardware can support and how many nodes you need to scale to your target audience.

**How can I use this to plan my instance fleet?**
You can tell your agent your target user count and your per-node capacity, and it will give you a specific number of instances to provision.

**Can it help me estimate my network costs?**
Yes, it calculates the network egress load for message broadcasting and the bandwidth overhead for heartbeat pings to help you predict costs.

**How does it calculate connection limits?**
It uses your hardware's memory constraints and the memory footprint per connection to give you a hard limit on concurrent users.

**Is this for real-time chat apps?**
Yes, it is specifically designed for real-time systems like chat, gaming, and live streaming where WebSocket connection limits are critical.

**Can it tell me how much bandwidth my heartbeats use?**
It provides a specific estimate of the bandwidth consumed by your ping and pong traffic so you can plan your steady-state network costs.

**How do I estimate the maximum connections for my server?**
Use the `estimate_max_connections` tool by providing your available RAM and the estimated memory footprint per connection.

**Can this help me plan for a global user base?**
Yes, use `calculate_required_servers` to determine how many server instances are needed to support your target total connection count.

**How is network overhead calculated?**
The `calculate_bandwidth_overhead` tool estimates the bandwidth consumed by heartbeat traffic based on your connection count and ping interval.