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CARTO MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes

Built by Vinkius GDPR 10 Tools SDK

The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect CARTO through 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 CARTO, list all available capabilities.",
    });
    console.log(text);
  } finally {
    await mcpClient.close();
  }
}

main();
CARTO
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* 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 CARTO MCP Server

Connect your CARTO platform to any AI agent and take full control of your cloud-native spatial analytics without touching the GIS interface.

The Vercel AI SDK gives every CARTO tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 tools through 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

  • Spatial SQL & Jobs — Command explicit SQL queries running directly against your BigQuery, Snowflake, or Redshift warehouse. Execute quick reads or spawn long-running, asynchronous batch transformations.
  • Geocoding & Batching — Convert unstructured strings into precise lat/lon points. Bulk-process 100s of addresses using CARTO's native Location Data Services (LDS) gracefully.
  • Isolines & Reachability — Calculate travel-time or distance polygons around origin points to instantly graph accessible zones via cars or walking.
  • Routing — Generate optimal vector geometry paths connecting two points on the globe, measuring both physical distance and travel time securely.
  • Data Management — Instruct your agent to list active mapping datasets or import massive external CSV/GeoJSON files directly via public URLs.

The CARTO MCP Server exposes 10 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 CARTO to Vercel AI SDK via MCP

Follow these steps to integrate the CARTO 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 10 tools from CARTO and passes them to the LLM

Why Use Vercel AI SDK with the CARTO MCP Server

Vercel AI SDK provides unique advantages when paired with CARTO 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 CARTO integration everywhere

03

Built-in streaming UI primitives let you display CARTO 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

CARTO + Vercel AI SDK Use Cases

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

01

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

02

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

03

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

04

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

CARTO MCP Tools for Vercel AI SDK (10)

These 10 tools become available when you connect CARTO to Vercel AI SDK via MCP:

01

calculate_isoline

The range parameter is in seconds for time-based isolines. Returns a GeoJSON polygon representing the reachable area. Use for service area analysis, store catchment zones, and logistics planning. Generate travel-time or travel-distance isoline polygons from a center point using the CARTO LDS Isolines API, producing reachability contours showing areas accessible within a specified time or distance threshold

02

calculate_route

Returns the route as GeoJSON with total distance (meters) and duration (seconds). Consumes LDS routing credits. Calculate the optimal driving route between two points using the CARTO LDS Routing API, returning distance, duration, and route geometry suitable for visualization on CARTO maps

03

create_async_sql_job

"}`. Returns a job_id that can be polled for completion status. Use for ETL operations, materialized view refreshes, and heavy geospatial computations. The job runs in your data warehouse and results are stored there. Submit a long-running SQL query as an asynchronous batch job via the CARTO SQL Job API, suitable for heavy spatial analytics, large table transformations, and complex multi-join operations that exceed the 60-second synchronous timeout

04

execute_sql_query

carto.com/api/v2/sql?q=`. The query runs synchronously with a 1-minute timeout. Use for quick analytical queries, spatial joins, and data exploration. For long-running queries exceeding 60 seconds, use the async job endpoint instead. Supports PostGIS/BigQuery spatial functions natively. Execute an arbitrary SQL query against your CARTO data warehouse connection using the SQL API v2, returning results as JSON rows directly from BigQuery, Snowflake, Redshift, or PostgreSQL

05

geocode_address

Returns latitude, longitude, and formatted address. Consumes LDS geocoding credits from your CARTO plan. Use sparingly for individual lookups; for bulk operations use the batch endpoint instead. Forward-geocode a single address string into geographic coordinates using the CARTO Location Data Services (LDS) geocoding endpoint, powered by TomTom or HERE depending on your CARTO plan configuration

06

geocode_batch_addresses

Designed for bulk processing of customer lists, store locators, and CRM datasets. Consumes LDS credits per address. Returns an array of geocoded results with match quality indicators. Batch-geocode multiple addresses in a single request using the CARTO LDS batch geocoding API, efficiently converting large address lists into coordinates without making individual API calls per address

07

get_import_status

Poll periodically until state becomes "complete" or "failure". On success, the response includes the table_name of the newly created dataset in your warehouse. Check the status of a previously initiated CARTO data import job, returning progress percentage, current state (uploading, importing, complete, failure), and any error details if the import encountered issues

08

import_external_file

"}`. Supports CSV, GeoJSON, Shapefile (zipped), KML, GPX, and Excel files. Returns an import_id for status tracking. The file is downloaded, parsed, and loaded into your connected data warehouse. Import an external data file (CSV, GeoJSON, Shapefile, KML) into your CARTO data warehouse by providing a publicly accessible URL, creating a new managed table that can be used for spatial analysis and visualization

09

list_map_datasets

Returns an array of dataset/visualization objects. Use to discover available data layers, check dataset freshness, and audit organization assets. List all visualization datasets (maps and tables) available in your CARTO organization, returning metadata including creation dates, privacy settings, table names, and row counts

10

poll_async_job_status

Poll periodically (every 5-10 seconds) until status changes to "done" or "failed". The response includes created_at, updated_at, and the original query for audit purposes. Check the execution status of a previously submitted CARTO async SQL job, returning the current state (pending, running, done, failed) and any error messages if the job encountered issues

Example Prompts for CARTO in Vercel AI SDK

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

01

"Execute a SQL query limiting to 10 rows on my 'retail_stores' dataset to check the schema."

02

"Take these 5 addresses in Madrid and bulk geocode them to lat/lon coordinates."

03

"Generate a 15-minute drive-time isoline around Times Square, New York."

Troubleshooting CARTO MCP Server with Vercel AI SDK

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

01

createMCPClient is not a function

Install: npm install @ai-sdk/mcp

CARTO + Vercel AI SDK FAQ

Common questions about integrating CARTO 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 CARTO to Vercel AI SDK

Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.