# Pointr MCP for AI Agents AI Agent Connect

> Pointr gives your AI agent the ability to see and navigate inside complex buildings. It connects your agent to high-precision indoor maps, allowing it to find specific points of interest, calculate walking paths across different floors, and monitor hardware like BLE beacons. It is the bridge between high-level instructions and the physical reality of indoor spatial data.

## Overview
- **Category:** iot-hardware
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_C80UHAWpnSofumPbQSlydWBY9PDBa9Vt5avQGQhi/ai-agent-connect
- **Tags:** indoor-positioning, wayfinding, ble-beacons, geofencing, spatial-intelligence, mapping

## Description

Pointr is an indoor mapping MCP that gives your agent the ability to navigate complex buildings. It connects your agent to high-precision indoor maps, allowing it to find specific points of interest, calculate walking paths across different floors, and monitor hardware like BLE beacons. It is the bridge between high-level instructions and the physical reality of indoor spatial data. Imagine trying to explain the layout of a massive airport or a multi-story shopping mall to someone who has never been there. You would have to describe every hallway, every elevator, and every store one by one. This Connector removes that friction by giving your AI agent a direct window into the actual floor plans and spatial data of your facilities. Instead of guessing where a gate is or how to get from the lobby to a specific retail unit, your agent can now query the network to find exact coordinates and navigate the best routes. It understands verticality, meaning it knows how to transition between floors and avoid physical obstacles like walls or restricted zones. Whether you are auditing your hardware mesh or planning foot traffic for a grand opening, this tool turns your AI into an expert on your physical environment. By adding this to your setup on Vinkius, you move away from static data and toward a dynamic understanding of indoor space. You can finally ask your agent to verify if a sensor is offline or to simulate how a crowd might move through a specific terminal, getting precise answers based on real-world mapping rather than generalities.

## Tools

### calculate_path
Compute the best walking path between two specific points. This provides accurate wayfinding that accounts for walls and floors.

### get_building
Get the full configuration for a specific Pointr building. This helps the agent understand the overall structure of a facility.

### get_level_map
Pull the floor plan data for a specific level of a building. Use this to see the exact layout of a single floor.

### get_poi
Get detailed information about a specific point of interest. This is useful for finding specific gates, stores, or amenities.

### list_beacons
Show all BLE beacons registered in the Pointr platform. Use this to audit your hardware mesh across a campus.

### list_buildings
List every building registered in the indoor intelligence network. This gives the agent a high-level view of all your managed sites.

### list_geofences
Show all indoor geofences configured in the platform. Use this to see where your proactive trigger zones are active.

### list_levels
List all floor levels for a specific building. This helps the agent understand how many floors a building has.

### list_pois
List all registered points of interest in the platform. Use this to see every designated location in your network.

### search_pois
Search for indoor points of interest using keywords. This lets the agent find specific items like restrooms or gates easily.

## Prompt Examples

**Prompt:** 
```
Can you find all the restrooms in the North Terminal?
```

**Response:** 
```
I've searched the North Terminal for you. Here are the restrooms found across all levels:

| Level | Location | Status |
| :--- | :--- | :--- |
| Ground | Near Gate A1 | Open |
| Level 2 | North Corridor | Open |
| Level 3 | Near Food Court | Maintenance |

Would you like the walking directions to the one closest to your current location?
```

**Prompt:** 
```
Which BLE beacons are currently offline in the main mall?
```

**Response:** 
```
I've checked the beacon network for the main mall. Here is the status of the hardware:

* **Node 442**: Offline (Floor 1)
* **Node 501**: Online (Floor 2)
* **Node 219**: Offline (Floor 1)
* **Node 883**: Online (Floor 3)

There are 2 beacons currently reporting as offline. Should I list their specific floor locations?
```

**Prompt:** 
```
What's the best way to walk from Gate A to the Food Court?
```

**Response:** 
```
The best walking path involves heading toward the elevators near Gate A, taking them up to Level 2, and then heading east. This route is approximately 140 meters and avoids the construction zone in the main lobby.
```

## Capabilities

### Find specific indoor locations
The agent can locate specific gates, stores, or amenities using simple keywords.

### Calculate multi-floor walking paths
Your agent can determine the best route between two points while accounting for stairs and elevators.

### List all registered buildings
The agent can see every building registered in your indoor intelligence network.

### Check beacon hardware status
You can ask the agent to verify where your physical network sensors reside and if they are active.

### Identify active geo-fences
The agent can pull the logical polygons mapping where your local alerts fire globally.

### Retrieve detailed floor plans
Your agent can access the floor plan map data for any specific building level.

## Use Cases

### Audit offline hardware
A facilities manager asks the agent to check all beacons in a terminal. The agent identifies which units are not reporting.

### Plan retail traffic
A planner asks for the best way to move people from a main gate to a store. The agent finds the best route across two floors.

### Find specific amenities
A user asks for all restrooms in a specific building. The agent finds and lists them by level.

### Extract layout data
An engineer needs to know the constraints of a new wing. The agent pulls the geometry for that specific floor.

## Benefits

- Stop manually searching through PDF floor plans by pulling layout data directly into your agent's context.
- Verify hardware health across entire campuses by checking every sensor in the network at once.
- Automate wayfinding for customers by generating precise walking directions that account for floor changes.
- Manage large-scale facility deployments more easily by seeing every registered site in a single query.
- Define precise alert zones for your operations by seeing where your triggers are active globally.

## How It Works

The bottom line is that your AI gains the ability to interact with and navigate complex indoor environments as if it had a map in its hands.

1. Add the Pointr connector to your Connector configuration
2. Introduce your Enterprise Bearer Token into the configuration vault
3. Begin instructing your agent to dissect and verify indoor mapping models

## Frequently Asked Questions

**How can Pointr help with indoor navigation?**
It lets your AI agent understand floor plans and calculate precise walking paths, including stairs and elevators.

**Can I use Pointr to manage my BLE beacons?**
Yes, you can ask your agent to list all registered beacons and check their status across your entire facility.

**Does Pointr support multi-floor mapping?**
Yes, it understands vertical architecture, so your agent can navigate between different levels and floors.

**Can I search for specific points of interest?**
You can ask the agent to find things like gates, stores, or restrooms using keywords.

**How do I use Pointr for facility auditing?**
You can have your agent cross-reference your beacon list against the building's floor geometry to spot hardware issues.

**Is Pointr good for large venues like airports?**
It is designed specifically for complex indoor spaces like airports, malls, and large corporate campuses.

**Can the agent calculate walking paths across multiple floors?**
Yes. When triggering `calculate_path` supplied with explicit coordinate pairings spanning different Level UUIDs, the Pointr engine bridges the wayfinding automatically. It factors in fixed transitions like elevators or stairs natively, feeding the Agent the comprehensive turn-by-turn array in JSON format seamlessly.

**Is it possible to extract the giant raw map shapes for a given floor?**
Absolutely. By initiating the query `get_level_map` tied securely to a single level UUID, the interface processes and downloads massive explicit geometries mapping out physical walls, traversable space nodes, and internal partitions explicitly generated by the Pointr pipeline.

**Can I search for specific stores or bathrooms using text queries?**
Yes. Pointr exposes dense fuzzy logic matching indexes. When the Agent executes `search_pois` feeding a literal keyword alongside the Target Building ID, it reliably unearths precisely mapped nodes conforming to 'Restroom', 'Exit', or custom store names embedded dynamically.