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Watershed Climate MCP Server for Vercel AI SDK 16 tools — connect in under 2 minutes

Built by Vinkius GDPR 16 Tools SDK

The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Watershed Climate through the Vinkius and every tool is available as a typed function — ready for React Server Components, API routes, or any Node.js backend.

Vinkius supports streamable HTTP and SSE.

typescript
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

async function main() {
  const mcpClient = await createMCPClient({
    transport: {
      type: "http",
      // Your Vinkius token — get it at cloud.vinkius.com
      url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    },
  });

  try {
    const tools = await mcpClient.tools();
    const { text } = await generateText({
      model: openai("gpt-4o"),
      tools,
      prompt: "Using Watershed Climate, list all available capabilities.",
    });
    console.log(text);
  } finally {
    await mcpClient.close();
  }
}

main();
Watershed Climate
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High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Watershed Climate MCP Server

Connect your Watershed Climate organization to any AI agent and take full control of your carbon measurement, reporting, and reduction workflows through natural conversation.

The Vercel AI SDK gives every Watershed Climate tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 16 tools through the Vinkius and stream results progressively to React, Svelte, or Vue components — works on Edge Functions, Cloudflare Workers, and any Node.js runtime.

What you can do

  • Data Uploads — Create upload containers, add activity data records (electricity, travel, shipping), and validate data quality
  • Batch Data Ingestion — Upload multiple activity records in batch with proper formatting and emission factor mapping
  • GHG Inventories — List and inspect greenhouse gas inventories with Scope 1, 2, and 3 emissions breakdowns
  • Emissions Measurements — Query calculated carbon footprint measurements filtered by inventory or year
  • Processing Tasks — Monitor async processing tasks from upload submissions with real-time status checks
  • Reports & Disclosures — List and access generated sustainability reports (CDP, TCFD, custom formats)
  • Reduction Targets — View configured emissions reduction targets aligned with SBTi and net-zero commitments

The Watershed Climate MCP Server exposes 16 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Watershed Climate to Vercel AI SDK via MCP

Follow these steps to integrate the Watershed Climate MCP Server with Vercel AI SDK.

01

Install dependencies

Run npm install @ai-sdk/mcp ai @ai-sdk/openai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the script

Save to agent.ts and run with npx tsx agent.ts

04

Explore tools

The SDK discovers 16 tools from Watershed Climate and passes them to the LLM

Why Use Vercel AI SDK with the Watershed Climate MCP Server

Vercel AI SDK provides unique advantages when paired with Watershed Climate through the Model Context Protocol.

01

TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box

02

Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime — same Watershed Climate integration everywhere

03

Built-in streaming UI primitives let you display Watershed Climate tool results progressively in React, Svelte, or Vue components

04

Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency

Watershed Climate + Vercel AI SDK Use Cases

Practical scenarios where Vercel AI SDK combined with the Watershed Climate MCP Server delivers measurable value.

01

AI-powered web apps: build dashboards that query Watershed Climate in real-time and stream results to the UI with zero loading states

02

API backends: create serverless endpoints that orchestrate Watershed Climate tools and return structured JSON responses to any frontend

03

Chatbots with tool use: embed Watershed Climate capabilities into conversational interfaces with streaming responses and tool call visibility

04

Internal tools: build admin panels where team members interact with Watershed Climate through natural language queries

Watershed Climate MCP Tools for Vercel AI SDK (16)

These 16 tools become available when you connect Watershed Climate to Vercel AI SDK via MCP:

01

create_upload

An upload is required before you can add data records to Watershed. After creating an upload, you add data records to it, validate the data, and then submit it for processing. The upload acts as a batch grouping mechanism for related activity data. You can optionally provide a name and description to identify the upload purpose. Create a new data upload container in Watershed

02

delete_upload_data_record

Use this to remove incorrect or unwanted data before validating and submitting the upload. This action cannot be undone. The record_id is obtained from list_upload_data_records. Delete a specific data record from an upload

03

get_inventory

Use the inventory_id from list_inventories to inspect detailed carbon footprint results and understand your organization's emissions composition. Get detailed information about a specific GHG inventory

04

get_report

Use the report_id from list_reports to access the full report details including generated files, disclosure frameworks covered, and emissions data summarized. Reports are typically generated after inventories are complete and validated. Get detailed information about a specific report

05

get_task_status

When you submit an upload for processing, a task is created and returns a task_id. Use this tool to check if the processing is complete, still in progress, or failed. Task status is useful for monitoring large data submissions that may take time to process. Check status of a processing task (e.g., upload submission)

06

get_upload

Use the upload_id from list_uploads to inspect details before adding data or submitting for validation. Get details of a specific data upload

07

list_inventories

An inventory represents your organization's carbon footprint measurement for a specific year, containing Scope 1 (direct), Scope 2 (energy), and Scope 3 (value chain) emissions data. Each inventory has a year, status, and total emissions calculated from submitted activity data. List all GHG inventories in your Watershed organization

08

list_measurements

Measurements represent the actual carbon footprint values derived from your uploaded activity data. You can filter by inventory_id to see measurements for a specific year's inventory, or by year to see measurements across all inventories for that year. Each measurement includes the activity type, emission factor used, and calculated CO2e value. List emissions measurements with optional filters

09

list_reduction_targets

Reduction targets define your organization's goals for decreasing emissions over time, often aligned with Science Based Targets initiative (SBTi) or net-zero commitments. Each target includes baseline year, target year, reduction percentage, and progress tracking. List all emissions reduction targets configured in your organization

10

list_reports

Reports are formatted outputs of your climate data for disclosure, analysis, or internal review. Reports can include CDP disclosures, TCFD reports, or custom carbon footprint summaries. Each report has metadata about its type, generation date, and scope. List all available reports in your Watershed organization

11

list_upload_data_records

Each record contains the activity data that will be processed into emissions measurements. Use this to review the data before validating and submitting the upload. List all data records in a specific upload

12

list_uploads

Uploads are containers for activity data that will be validated and processed into emissions measurements. Each upload can contain multiple data records representing activities like electricity usage, flights, or shipping. Use this to see all existing uploads and their IDs before adding data or submitting for processing. List all data uploads in your Watershed organization

13

submit_upload

This triggers Watershed's calculation engine to convert activity data into emissions measurements using appropriate emission factors. The upload must be validated successfully before submission. The response includes a task_id that can be used to track processing status via get_task_status. Processing may take some time depending on data volume. Submit a validated upload for emissions processing

14

update_upload_data_record

Use this to correct errors or modify activity data before validation and submission. The record_id is obtained from list_upload_data_records. The body should contain the complete updated record object with all required fields. Update a specific data record in an upload

15

upload_data_records

Each record represents an activity that generates emissions (e.g., electricity consumption, business travel, shipping). Records should follow Watershed's data format with fields like: activity_type, quantity, unit, start_date, end_date, location, etc. You can upload a single record or multiple records in a batch by providing an array of objects. Example record: { "activity_type": "electricity", "quantity": 1500, "unit": "kWh", "start_date": "2024-01-01", "end_date": "2024-01-31" } Upload activity data records to an existing upload container

16

validate_upload

Validation ensures data quality and prevents rejection during the submission phase. The response includes validation results with any errors or warnings that need to be addressed. Always validate before submitting to ensure successful processing. Validate data in an upload before submission

Example Prompts for Watershed Climate in Vercel AI SDK

Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Watershed Climate immediately.

01

"List all our GHG inventories and show me the total emissions for 2024."

02

"Create a new upload called 'Q1 2024 Electricity Data', add these 3 records: electricity usage for NYC office (50,000 kWh), London office (35,000 kWh), and São Paulo office (28,000 kWh) for January 2024, then validate and submit it."

03

"Show me our reduction targets and current progress toward our net-zero goal."

Troubleshooting Watershed Climate MCP Server with Vercel AI SDK

Common issues when connecting Watershed Climate to Vercel AI SDK through the Vinkius, and how to resolve them.

01

createMCPClient is not a function

Install: npm install @ai-sdk/mcp

Watershed Climate + Vercel AI SDK FAQ

Common questions about integrating Watershed Climate MCP Server with Vercel AI SDK.

01

How does the Vercel AI SDK connect to MCP servers?

Import createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.
02

Can I use MCP tools in Edge Functions?

Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.
03

Does it support streaming tool results?

Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.

Connect Watershed Climate to Vercel AI SDK

Get your token, paste the configuration, and start using 16 tools in under 2 minutes. No API key management needed.