CARTO MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect CARTO through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"carto": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using CARTO, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* 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.
LangChain's ecosystem of 500+ components combines seamlessly with CARTO through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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 LangChain 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 LangChain via MCP
Follow these steps to integrate the CARTO MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 10 tools from CARTO via MCP
Why Use LangChain with the CARTO MCP Server
LangChain provides unique advantages when paired with CARTO through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine CARTO MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across CARTO queries for multi-turn workflows
CARTO + LangChain Use Cases
Practical scenarios where LangChain combined with the CARTO MCP Server delivers measurable value.
RAG with live data: combine CARTO tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query CARTO, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain CARTO tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every CARTO tool call, measure latency, and optimize your agent's performance
CARTO MCP Tools for LangChain (10)
These 10 tools become available when you connect CARTO to LangChain via MCP:
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
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
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
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
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
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
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
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
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
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 LangChain
Ready-to-use prompts you can give your LangChain agent to start working with CARTO immediately.
"Execute a SQL query limiting to 10 rows on my 'retail_stores' dataset to check the schema."
"Take these 5 addresses in Madrid and bulk geocode them to lat/lon coordinates."
"Generate a 15-minute drive-time isoline around Times Square, New York."
Troubleshooting CARTO MCP Server with LangChain
Common issues when connecting CARTO to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersCARTO + LangChain FAQ
Common questions about integrating CARTO MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect CARTO with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect CARTO to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.