How to Use the IndoorAtlas (Indoor Positioning) MCP in Mastra AI
Build resilient location workflows with Mastra AI and the IndoorAtlas (Indoor Positioning) MCP Server.
Works with every AI agent you already use
…and any MCP-compatible client
Connect IndoorAtlas (Indoor Positioning) MCP to Mastra AI
Create your Vinkius account to connect IndoorAtlas (Indoor Positioning) to Mastra AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Mastra AI automated venue deployment
Chain your deployment steps using `create_venue` and `upload_floorplan_geojson` within a Mastra workflow. If an upload fails, you can define a retry policy to ensure the floorplan lands correctly. This setup allows for consistent site provisioning. You handle the logic of linking a new facility to its positioning data without manual intervention or oversight.
Positioning session analysis in Mastra AI
Use `list_positioning_sessions` to trigger automated audits of your facility traffic. Mastra AI can parse these sessions to identify dwell time patterns or path bottlenecks automatically. When a session finishes, the agent can fetch the full trace with `get_session_data`. This gives you the raw metrics needed to judge if your current radio map is performing as expected.
Conditional radio map maintenance
Detect calibration gaps by running `get_fingerprint_paths` and comparing the results against your floorplan area. If coverage is low, the workflow can alert a technician to walk the site again. Once the new data is captured, trigger the update using `trigger_map_generation`. The system handles the asynchronous wait time, only moving to the next workflow step once the map is ready.
Set up IndoorAtlas (Indoor Positioning) MCP in Mastra AI
Prerequisites
- Node.js 18+ and a TypeScript project
-
@mastra/mcp+@mastra/corepackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
npm install @mastra/mcp @mastra/coreplus your preferred model provider (e.g.@ai-sdk/openai). - 2
Configure the MCPClient
Create an
MCPClientwith your Vinkius endpoint as aURLobject. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. - 3
Discover and inject tools
Call
mcpClient.listTools()and spread the result into your agent'stoolsobject. All IndoorAtlas (Indoor Positioning) tools become native Mastra tools. - 4
Run with any model
Swap
openai("gpt-4o")for any AI SDK-compatible provider. Callagent.generate()and the agent routes tool calls through MCP automatically.
import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";
const mcpClient = new MCPClient({
id: "indooratlas-indoor-positioning-mcp-client",
servers: {
"indooratlas-indoor-positioning-mcp": {
url: new URL(
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
),
},
},
});
const agent = new Agent({
name: "IndoorAtlas (Indoor Positioning) Agent",
model: openai("gpt-4o"),
instructions: "You have access to IndoorAtlas (Indoor Positioning) tools.",
tools: {
...(await mcpClient.listTools()),
},
});
const result = await agent.generate(
"List recent IndoorAtlas (Indoor Positioning) transactions"
);
console.log(result.text); 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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Common questions about IndoorAtlas (Indoor Positioning) MCP in Mastra AI
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