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Connect WebSocket Capacity Planner to ChatGPT and Claude

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Plan your real-time infrastructure with precise connection and bandwidth math.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 4 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through WebSocket Capacity Planner.

  1. 01

    Calculate bandwidth overhead

    This capability estimates the specific bandwidth used by heartbeat ping and pong traffic. It helps you see the hidden cost of keeping connections alive.

  2. 02

    Calculate required servers

    Use this to find the exact number of server instances needed to support a specific target of global connections.

  3. 03

    Estimate broadcast load

    This capability calculates the network egress load generated when you broadcast messages across multiple channels.

  4. 04

    Estimate max connections

    This capability determines the maximum number of concurrent connections a single node can host based on your available memory.

Real work

What teams actually run

01

Capacity Planning

Determine if your current hardware can handle a sudden influx of new users.

02

Cost Optimization

Calculate the minimum number of servers needed to avoid over-provisioning.

03

Network Budgeting

Estimate the egress costs and bandwidth needs for high-frequency broadcast messages.

04

System Auditing

Check how much overhead heartbeat traffic is adding to your total network load.

One connector, every AI

WebSocket Capacity Planner works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put WebSocket Capacity Planner to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

706ms average. Fast in production.

WebSocket Capacity Planner is checked daily against the live service.

Daily averagePeak 975ms
Oct 3Today
Fastest day
594ms
Slowest day
975ms
14-day trend
Slowing+8%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 4 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of WebSocket Capacity Planner, so you can see the experience inside your AI.

It does not authenticate your account with WebSocket Capacity Planner. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

WebSocket Capacity Planner Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_A2KKR618IPEurqCafkvsVgIKXzk9F63mnDdpvJwf/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — WebSocket Capacity Planner capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "websocket-capacity-planner-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_A2KKR618IPEurqCafkvsVgIKXzk9F63mnDdpvJwf/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up WebSocket Capacity Planner in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work WebSocket Capacity Planner owners hand off.

This MCP is built for engineers managing real-time, high-concurrency systems.

  • 01

    DevOps Engineers

    They hand off scaling requirements to the AI to get instant fleet size estimates.

  • 02

    Backend Developers

    They use it to check if their proposed architecture can handle expected user loads.

  • 03

    Network Engineers

    They use the capability to calculate egress and heartbeat overhead for bandwidth planning.

FAQ

Questions WebSocket Capacity Planner owners ask.

  • 01

    What can this MCP calculate?

    It calculates maximum concurrent connections per node, required server fleet sizes, network egress load from broadcasts, and heartbeat bandwidth overhead.

  • 02

    Which AI clients can use this MCP?

    You can use this with any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code.

  • 03

    Do I need to host the MCP myself?

    No, Vinkius hosts and manages the MCP for you. You just connect your client and start using the capabilities.

  • 04

    How does it handle memory constraints?

    The estimate_max_connections capability uses your provided memory limits and per-connection footprint to find the connection ceiling.

  • 05

    Can it help with broadcast scaling?

    Yes, the estimate_broadcast_load capability calculates the egress load based on your message frequency and subscriber count.

  • 06

    How do I estimate the maximum connections for my server?

    Use the estimate_max_connections capability by providing your available RAM and the estimated memory footprint per connection.

  • 07

    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.

  • 08

    How is network overhead calculated?

    The calculate_bandwidth_overhead capability estimates the bandwidth consumed by heartbeat traffic based on your connection count and ping interval.

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