What can this MCP calculate?

It calculates initial setup costs, recurring maintenance and storage costs, and potential savings from optimization techniques like caching.

How does it help with RAG applications?

It models the Total Cost of Ownership for vector-based applications, helping you plan for the costs of embedding and maintaining your vector database.

Can I use this with Claude or Cursor?

Yes, you can connect this MCP to any compatible client including Claude, Cursor, and Windsurf.

Does it account for storage costs?

It can estimate maintenance costs, though specific storage fees will depend on the provider you choose to use.

How do I see the impact of caching?

You use the simulate_optimization_impact capability to see how much money you can save by applying batching and caching to your workflow.

How do I calculate the initial cost of embedding my data?

You can use the calculate_initial_setup_costs capability by providing the total number of items, the average tokens per item, and the cost per 1,000 tokens.

Can I estimate savings from using a cache?

Yes, the simulate_optimization_impact capability allows you to input a cache hit rate to see the potential reduction in monthly update costs.

Does this account for vector database storage fees?

Yes, the calculate_maintenance_costs capability includes a parameter for monthly storage cost per item to provide a complete recurring cost estimate.

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Connect Embedding Economics Calculator 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 vector database budgets with precision.

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 · 4 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through Embedding Economics.

01
Calculate initial setup costs
This capability determines the one-time expense required to embed a new dataset.
02
Calculate maintenance costs
Use this to estimate recurring costs for data updates and storage over a set timeframe.
03
Get cost summary report
This capability generates a high-level economic overview of your entire AI application's cost profile.
04
Simulate optimization impact
This capability evaluates potential savings gained by implementing batching and caching strategies.

Real work

What teams actually run

RAG Budgeting

Calculate the total cost of embedding a large knowledge base before deployment.

Cost Optimization

Run simulations to see if implementing a cache will pay for itself in reduced embedding fees.

Scaling Projections

Estimate how much monthly maintenance costs will rise as your dataset grows.

Vendor Comparison

Model how different token pricing and storage models affect your long-term TCO.

One connector, every AI

Embedding Economics 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 Embedding Economics 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

877ms average. Fast in production.

Embedding Economics is checked daily against the live service.

Daily averagePeak 1082ms

Oct 3Today

Fastest day: 732ms
Slowest day: 1082ms
14-day trend: Slowing+22%

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 Embedding Economics, so you can see the experience inside your AI.

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

Embedding Economics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_vIv6itu4zFeLNhPaaV8Ole867bKlxITRmagkFkHQ/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 — Embedding Economics capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "embedding-economics-calculator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_vIv6itu4zFeLNhPaaV8Ole867bKlxITRmagkFkHQ/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 Embedding Economics in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Embedding Economics owners hand off.

This MCP is built for technical professionals who need to bridge the gap between AI architecture and financial planning.

01
AI Developers
They use the capability to estimate the cost of new features before they write a single line of code.
02
Product Managers
They use the math to build accurate budget forecasts for RAG-based products.
03
FinOps Engineers
They use the optimization simulations to justify infrastructure changes.

FAQ

Questions Embedding Economics owners ask.

01
What can this MCP calculate?
It calculates initial setup costs, recurring maintenance and storage costs, and potential savings from optimization techniques like caching.
02
How does it help with RAG applications?
It models the Total Cost of Ownership for vector-based applications, helping you plan for the costs of embedding and maintaining your vector database.
03
Can I use this with Claude or Cursor?
Yes, you can connect this MCP to any compatible client including Claude, Cursor, and Windsurf.
04
Does it account for storage costs?
It can estimate maintenance costs, though specific storage fees will depend on the provider you choose to use.
05
How do I see the impact of caching?
You use the simulate_optimization_impact capability to see how much money you can save by applying batching and caching to your workflow.
06
How do I calculate the initial cost of embedding my data?
You can use the calculate_initial_setup_costs capability by providing the total number of items, the average tokens per item, and the cost per 1,000 tokens.
07
Can I estimate savings from using a cache?
Yes, the simulate_optimization_impact capability allows you to input a cache hit rate to see the potential reduction in monthly update costs.
08
Does this account for vector database storage fees?
Yes, the calculate_maintenance_costs capability includes a parameter for monthly storage cost per item to provide a complete recurring cost estimate.

Explore

More in Finance

Connect Embedding Economics 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.

01-04

Calculate initial setup costs

Calculate maintenance costs

Get cost summary report

Simulate optimization impact

What teams actually run

RAG Budgeting

Cost Optimization

Scaling Projections

Vendor Comparison

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

Embedding Economics Connector

Claude Desktop

AI Developers

Product Managers

FinOps Engineers

What can this MCP calculate?

How does it help with RAG applications?

Can I use this with Claude or Cursor?

Does it account for storage costs?

How do I see the impact of caching?

How do I calculate the initial cost of embedding my data?

Can I estimate savings from using a cache?

Does this account for vector database storage fees?

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