Documentation

Overview

Camino AI gives your applications real-world location intelligence through a simple, developer-friendly API. Ask questions in natural language and get structured, accurate location data instantly.

Natural Language

Query places the way humans think: "quiet cafes with wifi near downtown"

AI-Powered Ranking

Results ranked by actual relevance, not just proximity

Plug & Play

Works with any language or framework. Simple REST API + MCP support

Real-Time Data

OpenStreetMap data updated continuously worldwide

What Can You Build?

AI Travel Assistants — Help users find hotels, restaurants, and attractions
Real Estate Tools — Analyze neighborhoods, nearby amenities, commute times
Logistics Applications — Route optimization, delivery planning, fleet management
Chatbots & Agents — Ground LLM responses in real location data
Research Tools — Analyze geographic patterns, find patterns in POI data

Quick Start

Get up and running in under 5 minutes.

Create an Account
Sign up at getcamino.ai/login with your Google account. You'll get 1,000 free API calls per month.
Get Your API Key
Go to your Dashboard and create an API key. Copy it somewhere safe.
Make Your First Query
Try this curl command (replace YOUR_KEY with your actual key):

curl "https://api.getcamino.ai/query" \ -H "X-API-Key: YOUR_KEY" \ --data-urlencode query="coffee shops in Times Square" \ --data-urlencode lat="40.758" \ --data-urlencode lon="-73.985"
Parse the Response
You'll receive structured JSON with places, coordinates, distances, and an AI-generated summary.

Tip

Don't have coordinates? The API can infer location from well-known place names like "Times Square" or "Eiffel Tower".

Authentication

All API requests require authentication via an API key.

Using Your API Key

Include your API key in the X-API-Key header:

curl "https://api.getcamino.ai/query?query=..." \
  -H "X-API-Key: cam_your_api_key_here"
                

Or as a query parameter (useful for MCP):

curl "https://api.getcamino.ai/query?query=...&caminoApiKey=cam_your_key"

Rate Limits

Free tier: 1,000 calls/month, 30 requests/minute
Paid: Unlimited calls, 60 requests/minute

Natural Language Query

The core endpoint for finding places using natural language.

GET /query

Search for places using natural language queries with optional AI ranking.

Parameter	Type	Description
query *	string	Natural language search query
lat	float	Latitude (recommended for best results)
lon	float	Longitude (recommended for best results)
radius	int	Search radius in meters (default: 1000)
limit	int	Max results to return (default: 20, max: 100)
rank	bool	Use AI ranking (default: true)
answer	bool	Include AI-generated summary (default: true)

Example Response

{
  "query": "coffee shops in Times Square",
  "results": [
    {
      "name": "Blue Bottle Coffee",
      "lat": 40.7580,
      "lon": -73.9855,
      "address": "1 Times Square, New York",
      "distance_m": 120,
      "relevance_score": 0.95
    }
  ],
  "answer": "I found 12 coffee shops near Times Square...",
  "count": 12
}
                

Route Planning

Calculate routes between points with distance, duration, and turn-by-turn directions.

GET /route

Get directions between two points.

Parameter	Type	Description
start_lat *	float	Starting latitude
start_lon *	float	Starting longitude
end_lat *	float	Destination latitude
end_lon *	float	Destination longitude
mode	string	Transport mode: car, bike, foot (default: car)

Spatial Relationships

Understand the relationship between two locations — distance, direction, travel time.

POST /relationship

Analyze the spatial relationship between two points.

{
  "start": { "lat": 40.7580, "lon": -73.9855 },
  "end": { "lat": 40.7484, "lon": -73.9857 },
  "include": ["distance", "direction", "travel_time", "description"]
}
                        

Place Context

Get contextual information about what's around a specific location.

POST /context

Understand the surroundings of a location.

{
  "location": { "lat": 40.7580, "lon": -73.9855 },
  "radius": "500m",
  "context": "evaluating for a new office location"
}
                        

Journey Planning

Plan multi-stop trips with time budgets and transport constraints.

POST /journey

Create optimized multi-stop itineraries.

{
  "waypoints": [
    { "lat": 40.758, "lon": -73.985, "purpose": "Start at Times Square" },
    { "lat": 40.748, "lon": -73.985, "purpose": "Visit Empire State Building" }
  ],
  "constraints": {
    "transport": "walking",
    "time_budget": "2 hours"
  }
}
                        

MCP Server Integration

Camino provides a remote MCP (Model Context Protocol) server, allowing AI assistants like Claude to use location intelligence directly — no local installation required.

What is MCP?

Model Context Protocol is a standard that lets AI assistants use external tools. With Camino's MCP server, Claude can search for places, plan routes, and answer location questions natively.

Claude Desktop Configuration

Add this to your Claude Desktop config file:

{
  "mcpServers": {
    "camino-ai": {
      "command": "npx",
      "args": [
        "-y",
        "@anthropic-ai/mcp-remote@latest",
        "https://api.getcamino.ai/mcp/sse?caminoApiKey=YOUR_KEY"
      ]
    }
  }
}
                

Cursor IDE Configuration

Same configuration works for Cursor:

{
  "mcpServers": {
    "camino-ai": {
      "command": "npx",
      "args": [
        "-y",
        "@anthropic-ai/mcp-remote@latest",
        "https://api.getcamino.ai/mcp/sse?caminoApiKey=YOUR_KEY"
      ]
    }
  }
}
                

Available MCP Tools

camino_query — Search for places using natural language
camino_route — Get directions between points
camino_relationship — Analyze spatial relationships
camino_context — Get context about a location
camino_journey — Plan multi-stop trips

SDKs & Integrations

Camino works with any HTTP client. Here are some popular integrations:

📖

Python Example

import requests

response = requests.get(
    "https://api.getcamino.ai/query",
    headers={"X-API-Key": "YOUR_KEY"},
    params={
        "query": "best pizza near Central Park",
        "lat": 40.7829,
        "lon": -73.9654
    }
)
data = response.json()
print(data["answer"])
                

JavaScript Example

const response = await fetch(
  `https://api.getcamino.ai/query?query=coffee+shops&lat=40.758&lon=-73.985`,
  { headers: { 'X-API-Key': 'YOUR_KEY' } }
);
const data = await response.json();
console.log(data.answer);
                

Overview

Natural Language

AI-Powered Ranking

Plug & Play

Real-Time Data

What Can You Build?

Quick Start

Authentication

Using Your API Key

Rate Limits

Natural Language Query

Example Response

Route Planning

Spatial Relationships

Place Context

Journey Planning

MCP Server Integration

Claude Desktop Configuration

Cursor IDE Configuration

Available MCP Tools

SDKs & Integrations

OpenAPI Spec

LangChain

LlamaIndex

n8n

Python Example

JavaScript Example

Create your account

Documentation

Overview

Natural Language

AI-Powered Ranking

Plug & Play

Real-Time Data

What Can You Build?

Quick Start

Authentication

Using Your API Key

Rate Limits

Natural Language Query

Example Response

Route Planning

Spatial Relationships

Place Context

Journey Planning

MCP Server Integration

Claude Desktop Configuration

Cursor IDE Configuration

Available MCP Tools

SDKs & Integrations

OpenAPI Spec

LangChain

LlamaIndex

n8n

Python Example

JavaScript Example