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How to Use the Planet Labs MCP in Vercel AI SDK

Stream live satellite imagery searches directly into your React UI using the Planet Labs MCP Server and Vercel AI SDK.

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Works with every AI agent you already use

…and any MCP-compatible client

Planet Labs MCP on Cursor AI Code Editor MCP Client Planet Labs MCP on Claude Desktop App MCP Integration Planet Labs MCP on OpenAI Agents SDK MCP Compatible Planet Labs MCP on Visual Studio Code MCP Extension Client Planet Labs MCP on GitHub Copilot AI Agent MCP Integration Planet Labs MCP on Google Gemini AI MCP Integration Planet Labs MCP on Lovable AI Development MCP Client Planet Labs MCP on Mistral AI Agents MCP Compatible Planet Labs MCP on Amazon AWS Bedrock MCP Support
MCP Servers — Included with Plan
Vinkius runs on Vercel AI SDK

Connect Planet Labs MCP to Vercel AI SDK

Create your Vinkius account to connect Planet Labs to Vercel AI SDK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

GDPR Included with Plan

Key Capabilities

Stream Planet Labs MCP Server results

The `quick_search` tool queries the Planet catalog for PSScene and SkySat imagery using GeoJSON boundaries. When you wire this through the Vercel AI SDK, your users watch satellite metadata stream into the frontend the moment the search executes. You don't need to build a loading state. The AI client pulls acquisition dates and cloud cover percentages, pushing them straight to your Next.js components. Users can immediately verify image quality with `get_cloud_coverage`. If the area is obscured, your prompt can automatically trigger another search for a different date range. The agent evaluates the clear area percentage and displays only the usable results in your Svelte or Vue application.

Expose imagery assets directly

The `get_item_assets` tool retrieves the exact download URLs and file sizes for a specific satellite capture. Your Vercel AI SDK implementation can fetch these analytic or visual data products and render direct download links in the browser. You bypass the need to write custom backend handlers for the Planet API. To help users pick the right format, the `list_asset_types` tool provides definitions for every available product. The AI agent reads the descriptions and explains the difference between a visual display image and an analytic NDVI file right in the chat interface.

Render coverage statistics instantly

The `get_search_statistics` tool generates histograms of available imagery over a specific time period. Streaming this data through the Vercel AI SDK lets you build interactive charts that populate as the AI thinks. Users see exactly how many RapidEye or Sentinel-2 captures exist for their farm before they commit to downloading anything. You can pair this with `get_item_details` to show the exact acquisition conditions. The agent cross-references the historical availability with the metadata of specific items, giving users a complete picture of the satellite coverage without leaving your application.

Setup guide

Set up Planet Labs 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. 1

    Install dependencies

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

  2. 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. 3

    Discover and use tools

    Call mcpClient.tools() to auto-discover all Planet Labs tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.

  4. 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 Planet Labs transactions",
});

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

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Planet Labs. 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.

Why Choose Vinkius

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Built-in savings

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Single dashboard

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Common questions about Planet Labs MCP in Vercel AI SDK

Install @ai-sdk/mcp and use createMCPClient with an HTTP transport pointing to your Vinkius endpoint. Call mcpClient.tools() and pass the array to generateText or streamText. Always remember to call mcpClient.close() when the stream finishes.
Yes. Your agent can call the create_subscription tool to set up recurring imagery deliveries to a cloud storage bucket. The user simply types a request for daily updates, and the SDK handles the API execution.
It does. You can pass an authProvider to the MCP client configuration. This ensures the AI agent only accesses the imagery catalogs and saved searches authorized by the current user.
Pass the GeoJSON directly to quick_search. The Vercel AI SDK streams the resulting imagery items back in chunks. If the boundary returns thousands of images, you can configure the agent to ask the user to narrow the date range.
The server processes your GeoJSON boundaries and search coordinates purely in memory using a V8 Isolate Sandbox. This ephemeral environment destroys the context immediately after returning the search results, ensuring your proprietary areas of interest never touch persistent storage.

Start using the Planet Labs MCP today

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