How to Use the Greenspark MCP in Mastra AI

Build resilient climate workflows in Mastra AI. Automate carbon offsetting and impact tracking with built-in failure handling.

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Connect Greenspark MCP to Mastra AI

Create your Vinkius account to connect Greenspark to Mastra AI 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 Greenspark with Mastra AI

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Automate impact triggers in Mastra AI

Deploy `create_impact` as a step in your Mastra agent workflows to ensure every transaction has a corresponding environmental action. The workflow engine handles the execution flow. If the initial attempt hits a network snag, the engine manages the retry logic automatically. You don't have to write manual error handlers for simple API hiccups.

Handle climate webhooks with Mastra AI

Use `create_webhook` to register listeners for your environmental data. When an impact is confirmed, your Mastra agent receives the update and triggers subsequent business logic. This keeps your agents in the loop without constant polling. You define the logic once, and the server notifies your agent when the climate action finishes.

Conditional climate logic for Mastra AI

Branch your agent decisions based on `get_impact_summary` data. You can decide whether to prompt a user for an additional offset based on their historical footprint. Your agents act on real data. By feeding these tools into the workflow engine, you build a system that responds intelligently to the user's environmental profile.

Setup guide

Set up Greenspark MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Greenspark tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "greenspark-mcp-client",
  servers: {
    "greenspark-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Greenspark Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Greenspark tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Greenspark transactions"
);
console.log(result.text);

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Greenspark. 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 Greenspark MCP in Mastra AI

You register the server as a tool source in your agent configuration. Mastra AI then treats these functions as native steps in your pipeline.

Yes, you configure the retry policy in your workflow definition. It handles transient failures without manual intervention.

Your credentials remain isolated. The agent only interacts with the tools you explicitly expose through the server configuration.

You check the agent execution logs. Every tool call and response is recorded, showing you the exact input and output for each climate action.

It accesses your transaction-level impact records and project details. This data is strictly used to process offsets and monitor your environmental progress.

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