How to Use the Climatiq Carbon Calculations MCP in Vercel AI SDK

Q: How do I handle high-volume carbon requests using Climatiq Carbon Calculations with Vercel AI SDK?

Use the batchestimateemissions tool to send up to 100 calculations in one payload. This prevents your Edge Functions from timing out and keeps the streaming response active.

Q: Can I stream Climatiq Carbon Calculations data directly to React components via Vercel AI SDK?

Yes. You pass the MCP tools to streamText and use UI components to display the raw carbon metrics as they arrive.

Q: How do I configure the Climatiq Carbon Calculations MCP Server inside a Vercel AI SDK route handler?

Install @ai-sdk/mcp and instantiate the MCP client using the Vinkius HTTP endpoint. Pass the tools directly to your generation call and close the connection when the stream ends.

Q: What happens if a user inputs an unsupported unit of measure?

The agent calls listunits to check acceptable formats. It then corrects the user's input before sending the final parameters to the calculation tools.

Pipe real-time carbon calculations directly into your Next.js frontend using the Vercel AI SDK.

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Connect Climatiq Carbon Calculations MCP to Vercel AI SDK

Create your Vinkius account to connect Climatiq Carbon Calculations to Vercel AI SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Climatiq Carbon Calculations with Vercel AI SDK

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Real-time carbon estimates in your streaming UI

The `estimate_emissions` tool calculates carbon footprints for specific activities and sends the data straight to your Vercel AI SDK stream. Your users see emission math resolve live on their screens instead of staring at a blank loading state. By combining this MCP Server with `streamText`, you bypass the typical API lag. The agent grabs the emission parameters, calls the tool, and renders the carbon footprint output instantly inside your React components.

Batch calculations without UI freezes

The `batch_estimate_emissions` tool processes up to 100 emission calculations in a single request, letting your Vercel AI SDK client handle heavy data loads. It maps complex arrays of activities to their carbon impact without blocking the main browser thread. You pass this tool to `generateText` alongside your user's uploaded spreadsheets. The client crunches the bulk carbon numbers on edge functions and renders the structured JSON array directly into interactive charts.

Instant emission factor search

The `search_emission_factors` tool finds exact carbon coefficients in the Climatiq database based on your user's natural language queries. Your Vercel AI SDK frontend displays these factors instantly as the user types their activity details. Instead of hardcoding static values, your agent queries this MCP Server to pull live regional data. It makes your carbon tracking forms dynamic, adjusting units and years on the fly based on real Climatiq database records.

Setup guide

Set up Climatiq Carbon Calculations MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all Climatiq Carbon Calculations tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent Climatiq Carbon Calculations transactions",
});

console.log(text);
await mcpClient.close();

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Climatiq. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Climatiq Carbon Calculations MCP in Vercel AI SDK

Use the `batch_estimate_emissions` tool to send up to 100 calculations in one payload. This prevents your Edge Functions from timing out and keeps the streaming response active.

Yes. You pass the MCP tools to `streamText` and use UI components to display the raw carbon metrics as they arrive.

Install `@ai-sdk/mcp` and instantiate the MCP client using the Vinkius HTTP endpoint. Pass the tools directly to your generation call and close the connection when the stream ends.

The agent calls `list_units` to check acceptable formats. It then corrects the user's input before sending the final parameters to the calculation tools.

Vinkius runs this MCP Server in an isolated V8 sandbox. Your raw activity parameters and carbon calculation payloads never touch public logs and are wiped immediately after the execution finishes.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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