Use AI Inference Monitoring Economics with your AI.
Connect your account once and let the AI you already use work with it, without building another integration. Quantify the financial impact and operational value of AI inference monitoring.
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.
Complete set · 4 capabilities
The complete AI Inference Monitoring Economics capability set.
These are the exact actions your AI can choose when you ask it to work with AI Inference Monitoring Economics.
01-04
4 capabilities in this set.
Part of 4 available through AI Inference Monitoring Economics.
- 01
Calculate coverage and confidence
Evaluates the statistical sufficiency of the monitoring strategy
- 02
Calculate monitoring unit cost
Determines the normalized cost of monitoring per million inferences
- 03
Calculate mttr value impact
Calculates the financial value gained from reducing the time to detect and resolve inference issues
- 04
Generate economic summary
Provides a high-level overview of the monitoring ROI (Return on Investment)
One connector, every AI
AI Inference Monitoring 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.
Claude
ChatGPT
Gemini
Perplexity
Grok
Microsoft Copilot
Cursor
VS Code
Windsurf
JetBrains
Cline
LangChain
Vercel AI SDK
Lovable
Z.ai
Raycast
Qwen Code
Kimi Code
Le ChatBuilding your own app? The connector is yours to use.
You don't need a client to put AI Inference Monitoring 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
906ms average. Fast in production.
AI Inference Monitoring Economics is checked daily against the live service.
- Fastest day
- 906ms
- Slowest day
- 937ms
- 14-day trend
- Stable-3%
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 AI Inference Monitoring Economics, so you can see the experience inside your AI.
It does not authenticate your account with AI Inference Monitoring Economics. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.
AI Inference Monitoring Economics Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_NEe8ce3WADfd8qm8DT8it7hEg5DciWYWPhkSFbKi/mcpClaude 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 — AI Inference Monitoring Economics capabilities are ready to use.
{
"mcpServers": {
"ai-inference-monitoring-economics-mcp": {
"url": "https://edge.vinkius.com/vk_preview_NEe8ce3WADfd8qm8DT8it7hEg5DciWYWPhkSFbKi/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? link.label
FAQ
Questions AI Inference Monitoring Economics owners ask.
- 01
How do I calculate the cost per million inferences?
Use the calculate_monitoring_unit_cost capability. It takes your total inference volume, logging volume, anomaly detection costs, and alerting costs to provide a normalized cost metric.
- 02
Can I model different sampling strategies?
Yes. The calculate_monitoring_unit_cost and calculate_coverage_and_confidence capabilities both accept a samplingRatio to account for partial monitoring coverage.
- 03
How is the MTTR value calculated?
The calculate_mttr_value_impact capability calculates savings by multiplying the reduction in Mean Time To Recovery (MTTR) by the hourly cost of downtime.
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