Vinkius
IndoorAtlas

Pinpoint people or assets inside any building.
Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
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Works with every AI agent you already use

…and any MCP-compatible client

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Connect to your AI in seconds.

IndoorAtlas helps you manage and analyze indoor location services for commercial buildings. List venues, upload floor plans, and run positioning models from raw signal data.

Get full control over your building's digital twin by connecting it directly to any AI client.

What your AI can do

Upload floorplan geojson

Accepts and uploads a new floor map as a GeoJSON file, geo-referencing it to make it ready for accurate positioning overlays.

Create venue

Sets up a new building container in IndoorAtlas, requiring you to specify the name, entrance coordinates, and initial setup parameters.

Trigger map generation

Initiates the server-side computation that creates the positioning model for a specific floor plan using collected signal data.

+ 7 more capabilities included
Inventory Building Locations

List all physical venues in your organization and inspect a venue's detailed metadata, including its coordinate system and floor count.

Upload and Align Floor Plans

Import new facility maps as GeoJSON files and correctly align them to real-world coordinates for accurate positioning overlays.

Calibrate the Positioning Map

Run signal fingerprinting walk paths to check coverage and generate the necessary models that allow location tracking to work on a specific floor.

Analyze Occupancy History

Retrieve full positioning session data, giving you timestamped coordinates to analyze where people spent their time or how often they moved through certain areas.

Determine Live Location from Signals

Calculate a device's estimated indoor position by submitting observed Wi-Fi signal strengths, useful when mobile SDK integration isn't possible.

Compatible AI Apps

OAuth 2.0 Compatible
Vinkius runs on Claude Claude
Vinkius runs on ChatGPT ChatGPT
Vinkius runs on Cursor Cursor
Vinkius runs on Gemini Gemini
Vinkius runs on VS Code VS Code
Vinkius runs on JetBrains JetBrains
Vinkius runs on Vercel Vercel
Vinkius runs on Zendesk Zendesk
+ any other MCP app
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AI Agent

IndoorAtlas (Indoor Positioning) MCP: 10 Tools

These tools let you define physical spaces, map out facility blueprints, simulate signal tracking, and analyze movement data across entire buildings.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using IndoorAtlas (Indoor Positioning) on Vinkius

Upload Floorplan Geojson

Accepts and uploads a new floor map as a GeoJSON file, geo-referencing it to make it ready for accurate positioning overlays.

Create Venue

Sets up a new building container in IndoorAtlas, requiring you to specify the name...

Trigger Map Generation

Initiates the server-side computation that creates the positioning model for a...

Get Fingerprint Paths

Retrieves the specific routes surveyors walked for calibration as GeoJSON, helping...

Get Session Data

Fetches the full track record of a single positioning session, including all...

Get Venue Details

Pulls detailed metadata on a specific venue, reporting its total mapped area, floor count, and current calibration status before deployment.

List Floorplans

Returns a list of every floor plan uploaded to the venue, detailing their dimensions, floor number, and whether mapping is ready for use.

List Positioning Sessions

Provides an indexed list of historical tracking sessions by returning IDs, start/end...

List Venues

Lists all buildings registered in your account, giving you the ID, name, and...

Position From Wifi Scan

Calculates an estimated indoor location by accepting observed Wi-Fi signal strengths...

Connect to your AI in seconds. Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Claude AI

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The IndoorAtlas integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

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Start building

Make Your AI Do More

Start with IndoorAtlas (Indoor Positioning), then connect any of our 5,000+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,000+ others, all in one place
  • Add new capabilities to your AI anytime you want
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  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog every week
IndoorAtlas MCP server cover

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

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Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This connection provides 10 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

Manually tracking movement across multiple building floors takes hours.

Right now, if you want to analyze where people moved through your campus over six months, you have to export data from the local monitoring system. You then copy those thousands of latitude/longitude points into a separate analysis tool and manually correlate them with floor plans and time stamps. It's tedious work involving dozens of tabs just to find out if people used the new elevator bank.

With this MCP, your agent handles the entire data pipeline. You tell it what you want—say, 'Show me traffic density near the main atrium.' The system pulls all necessary positioning session data, correlates it with every floor plan uploaded, and delivers the analysis directly to you.

IndoorAtlas (Indoor Positioning) MCP gives you full control over your location data.

The manual process of setting up a new wing involves submitting raw GeoJSON files, triggering the radio map generation in one window, and then manually verifying that all coordinates are properly anchored to real-world points. This is an iterative nightmare.

Now, you upload your floor plan via `upload_floorplan_geojson`, trigger the model computation with `trigger_map_generation` through a single conversation thread, and have the system handle the rest of the complex geometry alignment for you.

What your AI can actually do with this

You can take complete control of smart building infrastructure without needing a dedicated GIS team on retainer. This MCP connects your entire facility management system—from floor plan storage to real-time tracking analysis—to your agent. You start by defining the physical space, listing all available venues and uploading precise GeoJSON floor plans.

Once the map is set up, you can trigger the complex radio map generation process using signal data. From there, your agent tracks anything inside: determine a device's location simply from an incoming Wi-Fi scan or retrieve historical paths of people over weeks. You’ll find that Vinkius makes connecting these specialized services simple; instead of switching between three different platforms to analyze occupancy, you handle everything through natural conversation.

Built · Hosted · Managed by Vinkius IndoorAtlas - Indoor Positioning MCP
Server ID 019d75b9-2f40-71f3-96aa-134d54050017
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Questions you might have

How do I start the map generation process for a new floor plan? +

Use the trigger_map_generation tool with your Floorplan ID. This initiates the server-side computation that creates the positioning model. It's a critical step before indoor positioning can work on that level.

Can I determine a position using Wi-Fi scans through my agent? +

Yes. The position_from_wifi_scan tool allows you to submit observed Wi-Fi signal strengths. Your agent will return estimated coordinates and floor level, which is perfect for server-side positioning logic.

How can I analyze visitor traffic patterns in our building? +

Use the list_positioning_sessions tool to retrieve historical traces. Your agent can help you analyze occupancy patterns and dwell times by processing the timestamped coordinate fixes from past sessions.

How does using the list_venues tool help me discover all potential locations for mapping? +

It returns an array of every registered facility, providing their IDs, names, and geographic coordinates. Always call this first to confirm which buildings are ready before attempting to retrieve specific floor plan or session data.

When I use upload_floorplan_geojson, what specific GeoJSON structure must the file have? +

The uploaded document needs to be a valid GeoJSON that geo-references the indoor map image. This process ties the digital floor plan directly to real-world coordinates, making accurate positioning possible.

If I call get_session_data for years of records, how big is the output data set? +

The tool returns a full position trace as thousands of timestamped fixes. Be aware that your AI client needs robust memory handling to process potentially massive amounts of positional coordinate data.

What should I check if there are gaps in my signal mapping using get_fingerprint_paths? +

The output GeoJSON shows all recorded walk paths. You analyze this data layer to pinpoint specific areas or zones that lack coverage and require additional physical surveying runs for better accuracy.

After listing floor plans with list_floorplans, what's the necessary next step to actually enable positioning? +

Listing only provides metadata. You must use those IDs to upload the plan via upload_floorplan_geojson and then explicitly trigger map generation before any positioning data will work.

Built & Managed by Vinkius 30s setup 10 tools

We've already built the connector for IndoorAtlas. Just plug in your AI agents and start using Vinkius.

No hosting. No infrastructure. No complex setup.
All 10 tools are live and waiting. You're up and running in seconds.

Vinkius runs on Claude Claude
Vinkius runs on ChatGPT ChatGPT
Vinkius runs on Cursor Cursor
Vinkius runs on Gemini Gemini
Vinkius runs on Windsurf Windsurf
Vinkius runs on VS Code VS Code
Vinkius runs on JetBrains JetBrains
Vinkius runs on Vercel Vercel
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