How does this MCP help with LLM inference?

It provides a mathematical engine to calculate how much faster and cheaper your inference becomes when using speculative decoding.

Can I use this with Cursor or Windsurf?

Yes, any MCP-compatible client like Cursor, Windsurf, or VS Code can use this capability once connected through Vinkius.

What metrics does it actually calculate?

It calculates speedup ratios, effective throughput, optimal draft lengths, memory overhead, and monetary savings.

Do I need to provide my own model weights?

No, this MCP only performs calculations based on the performance metrics you provide, such as tokens per second and acceptance rates.

Is this for real-time monitoring?

It is a calculation engine designed for modeling and optimization rather than a real-time telemetry capability.

How do I know if my speculative decoding setup is efficient?

You can use the calculate_performance_metrics capability. It flags a configuration as inefficient if the speedup ratio is less than 1.5 or if the acceptance rate falls below 0.5.

Can I find the best draft length for my specific model pair?

Yes, the optimize_speculation_parameters capability iterates through possible draft lengths to find the one that maximizes effective throughput for your given parameters.

How much money can I save by using this optimization?

By using calculate_operational_impact, you can input the time saved during inference and your hardware cost per second to get an exact estimate of your cost savings.

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Connect Speculative Decoding Calculator to your AI

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. Find the exact draft length to maximize your inference throughput.

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.

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.

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 · 3 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-03

3 capabilities in this set.

Part of 3 available through Speculative Decoding Calculator.

01
Calculate operational impact
This capability estimates the total memory overhead and monetary savings for your inference operations.
02
Calculate performance metrics
This capability calculates speedup ratios and effective throughput based on your model speeds and acceptance rates.
03
Optimize speculation parameters
Use this to find the specific draft length that yields the highest throughput for your given constraints.

Real work

What teams actually run

Deployment Planning

Determine if adding a small draft model is worth the memory cost before you deploy to production.

Cost Reduction

Calculate how much a specific speculative decoding setup will lower your monthly API or compute bill.

Performance Benchmarking

Compare different draft model/target model pairings to see which combination yields the highest speedup.

Latency Tuning

Find the sweet spot where draft length maximizes throughput without increasing per-token latency too much.

One connector, every AI

Speculative Decoding Calculator 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.

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

You don't need a client to put Speculative Decoding Calculator 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

859ms average. Fast in production.

Speculative Decoding Calculator is checked daily against the live service.

Daily averagePeak 1011ms

Oct 3Today

Fastest day: 578ms
Slowest day: 1011ms
14-day trend: Slowing+11%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 3 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 Speculative Decoding Calculator, so you can see the experience inside your AI.

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

Speculative Decoding Calculator Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_XYWoPCFlNTCi1nCY0hLcYF1OVsVPSrlw38p6boSh/mcp

Claude Desktop

Follow the steps below to connect in seconds.

1In Claude Desktop, open Settings → Connectors.
2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3Click Add and start a new chat — Speculative Decoding Calculator capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "speculative-decoding-calculator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_XYWoPCFlNTCi1nCY0hLcYF1OVsVPSrlw38p6boSh/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 Speculative Decoding Calculator in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Speculative Decoding Calculator owners hand off.

This is built for engineers managing large scale LLM inference workloads who need to justify hardware or configuration changes.

01
ML Engineers
They hand off model performance data to the MCP to find the best deployment configurations.
02
AI Infrastructure Leads
They use the capability to project cost savings and hardware requirements for scaling inference.
03
LLM Researchers
They use it to model the theoretical limits of speculative decoding for new model architectures.

FAQ

Questions Speculative Decoding Calculator owners ask.

01
How does this MCP help with LLM inference?
It provides a mathematical engine to calculate how much faster and cheaper your inference becomes when using speculative decoding.
02
Can I use this with Cursor or Windsurf?
Yes, any MCP-compatible client like Cursor, Windsurf, or VS Code can use this capability once connected through Vinkius.
03
What metrics does it actually calculate?
It calculates speedup ratios, effective throughput, optimal draft lengths, memory overhead, and monetary savings.
04
Do I need to provide my own model weights?
No, this MCP only performs calculations based on the performance metrics you provide, such as tokens per second and acceptance rates.
05
Is this for real-time monitoring?
It is a calculation engine designed for modeling and optimization rather than a real-time telemetry capability.
06
How do I know if my speculative decoding setup is efficient?
You can use the calculate_performance_metrics capability. It flags a configuration as inefficient if the speedup ratio is less than 1.5 or if the acceptance rate falls below 0.5.
07
Can I find the best draft length for my specific model pair?
Yes, the optimize_speculation_parameters capability iterates through possible draft lengths to find the one that maximizes effective throughput for your given parameters.
08
How much money can I save by using this optimization?
By using calculate_operational_impact, you can input the time saved during inference and your hardware cost per second to get an exact estimate of your cost savings.

Explore

More in Optimization

Connect Speculative Decoding Calculator to Claude, Cursor, ChatGPT & more

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

Each Connector runs inside its own sealed environment.

One switch stops every agent. Instantly.

Spending limits that pause instead of surprise.

We ship only the actions that matter.

01-03

Calculate operational impact

Calculate performance metrics

Optimize speculation parameters

What teams actually run

Deployment Planning

Cost Reduction

Performance Benchmarking

Latency Tuning

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

Speculative Decoding Calculator Connector

Claude Desktop

ML Engineers

AI Infrastructure Leads

LLM Researchers

How does this MCP help with LLM inference?

Can I use this with Cursor or Windsurf?

What metrics does it actually calculate?

Do I need to provide my own model weights?

Is this for real-time monitoring?

How do I know if my speculative decoding setup is efficient?

Can I find the best draft length for my specific model pair?

How much money can I save by using this optimization?

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