Use Methane Emission Quantification with your AI.
Connect your account once and let the AI you already use work with it, without building another integration. Quantify methane emissions and intensity for oil and gas operations.
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 Methane Emission Quantification capability set.
These are the exact actions your AI can choose when you ask it to work with Methane Emission Quantification.
01-04
4 capabilities in this set.
Part of 4 available through Methane Emission Quantification.
- 01
Audit equipment compliance
Checks if the current equipment configuration meets specific methodology thresholds (EPA or OGMP)
- 02
Calculate emission intensity
Evaluates the relative environmental impact of operations by normalizing emissions against production volume
- 03
Calculate total emissions
Determines the aggregate methane mass emitted by an entire facility or operational area
- 04
Identify reduction opportunities
Simulates how much methane could be saved by upgrading specific equipment
One connector, every AI
Methane Emission Quantification 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 Methane Emission Quantification 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
867ms average. Fast in production.
Methane Emission Quantification is checked daily against the live service.
- Fastest day
- 867ms
- Slowest day
- 867ms
- 14-day trend
- Stable0%
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 Methane Emission Quantification, so you can see the experience inside your AI.
It does not authenticate your account with Methane Emission Quantification. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.
Methane Emission Quantification Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_KE7rFcFGDxdhvE2hXoCtQYqQKNV3J49wqBjBaYCG/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 — Methane Emission Quantification capabilities are ready to use.
{
"mcpServers": {
"methane-emission-quantification-mcp": {
"url": "https://edge.vinkius.com/vk_preview_KE7rFcFGDxdhvE2hXoCtQYqQKNV3J49wqBjBaYCG/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 Methane Emission Quantification owners ask.
- 01
Which regulatory standards are supported?
The server supports both EPA GHGI and OGMP methodologies for compliance auditing.
- 02
How can I simulate emission reductions?
You can use the identify_reduction_opportunities capability by providing your current inventory and potential upgrade scenarios.
- 03
Can I use real sensor data?
Yes, providing measurement data allows the capabilities to prioritize actual sensor readings over factor-based estimates.
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