What is an MCP Server?

Model Context Protocol (MCP) standardizes how AI assistants interact with tools and APIs. With MCP, documentation can be exposed as a structured resource that assistants understand and query programmatically.

MCP is an open standard that allows AI applications to securely access external data sources and tools. The TelemetryOS Documentation MCP server provides AI agents with:

Direct API access to TelemetryOS Documentation functionality
Documentation search capabilities
Real-time data from your TelemetryOS Documentation account
Code generation assistance for TelemetryOS Documentation integrations

It facilitates the standard communication between generative AI apps and the data they utilize, to simplify and accelerate the development of accurate and robust AI systems.

This open standard enables AI language models to connect to external tools, APIs, and data sources in a structured way. By providing discoverable endpoints and well-defined schemas, MCP servers allow AI models to retrieve up-to-date, context-specific information or perform actions in real time—without relying solely on pre-trained knowledge.

The TelemetryOS Documentation MCP server provides direct API access to TelemetryOS documentation functionality, comprehensive documentation search capabilities, real-time data when authenticated and authorized, and code generation assistance for documentation-integrated workflows.

How It Works

An MCP server functions like a helper service that sits between an AI (such as ChatGPT) and the tools or data it needs access to.

Think of it as a translator and connector that operates by first telling the AI what tools and information are available. The server then explains how to ask for that information, including what commands, parameters, or formats to use. When the AI makes a request, the MCP server fetches the data or performs the action and sends the results back to the requesting system.

For example, if the AI needs to check your device status, update an app, or pull data from a database, the MCP server handles the actual communication with those systems and makes the operations happen—following rules you've established in advance.

In short, an MCP server gives AI a safe, structured way to use real systems and live data instead of relying on pre-trained knowledge or making educated guesses.

We have created a dedicated MCP server that connects to our OpenAPI specification and utilizes search functionality. This creates a bridge between the documentation and AI assistants, making our help documentation instantly more accessible and understandable to AI tools.

The TelemetryOS Documentation Model Context Protocol (MCP) server enables AI-powered code editors like Cursor and Windsurf, plus general-purpose tools like Claude Desktop, to interact directly with your TelemetryOS Documentation API and documentation.

Use Cases

The TelemetryOS MCP server supports various practical applications in modern AI-assisted workflows.

Real-time data retrieval enables assistants to pull live stats, metrics, or logs from connected systems. For example, current CPU usage checks of servers or retrieval of sales numbers occurs through natural language queries.

Device management capabilities allow you to list devices, check operational status, or group them for targeted actions. This includes viewing all screens in a retail network and identifying which ones are offline or require attention.

Content deployment functionality supports pushing apps, media, or configurations to connected devices. New promotional video deployment to all digital signage devices in specific regions occurs via simple commands through AI assistants.

Playlist or schedule management enables you to assign or update content schedules in a digital signage network. The system can automatically switch from a morning playlist to an evening playlist at a predetermined time.

Searchable knowledge base access provides structured access to documentation or FAQs. When someone asks "How do I reset a TelemetryOS device?" the system pulls the exact procedure from your documentation and presents it contextually.

Workflow automation supports triggering pre-approved actions such as restarting a service or running diagnostics. Remote digital signage player restarts when devices become unresponsive occur through natural language interaction with AI assistants.

Domain-specific functions support specialized industry needs across various sectors. In healthcare, this might include booking appointments or retrieving patient education material. Logistics operations support shipment and delivery schedule tracking. Aviation contexts provide access to live flight status information.

Reporting and analytics capabilities enable on-demand report or analytics summary requests from connected systems. Monthly content performance report generation for all campaign screens occurs through AI assistant queries.

An MCP server transforms an AI assistant from a static question-answer tool into an active, real-time operations partner. Proper configuration and documentation enables direct, controlled AI access to business-critical systems.

TelemetryOS Documentation MCP Server Setup

TelemetryOS Documentation hosts a remote MCP server at docs.telemetryos.com/mcp. Configure your AI development tools to connect to this server. If your APIs require authentication, you can pass in headers via query parameters or however headers are configured in your MCP client.

Add to~/.cursor/mcp.json:

{
  "mcpServers": {
    "telemetryos-documentation": {
      "url": "https://docs.telemetryos.com/mcp"
    }
  }
}

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Access to private data requires valid credentials. Configure authentication in your MCP client before querying account-specific information.

MCP Connection Verification

MCP server connection verification confirms correct configuration and functional integration between AI tools and TelemetryOS Documentation endpoints.

Chat sessions with AI assistants (Cursor, Windsurf, Claude Desktop) provide testing interfaces for MCP functionality. Documentation queries test basic connectivity: "How do I [common use case]?" or "Show me an example of [API functionality]" or "Create a [integration type] using TelemetryOS Documentation."

Successfully configured assistants query documentation programmatically through MCP endpoints. With proper authentication, assistants additionally access account-specific data through authenticated API calls. This integration enables documentation-assisted development workflows within AI-powered coding environments.

Testing Your MCP Setup

Once configured, you can test your MCP server connection:

Open your AI editor (Cursor, Windsurf, etc.)
Start a new chat with the AI assistant
Ask about TelemetryOS Documentation - try questions like:
- "How do I [common use case]?"
- "Show me an example of [API functionality]"
- "Create a [integration type] using TelemetryOS Documentation"

The AI should now have access to your TelemetryOS Documentation account data and documentation through the MCP server.