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Quick Start Guide

Get up and running with Shinzo Platform in just a few minutes. This guide will walk you through instrumenting your MCP server and viewing product insights in the dashboard.

Prerequisites

Choose one based on your language: TypeScript/JavaScript: Python: Both:

Step 1: Install the SDK

Install the Shinzo instrumentation SDK in your MCP server project:

Step 2: Get Your Ingest Token

  1. Sign up or log in at app.shinzo.ai.
  2. Navigate to Settings → Ingest Tokens.
  3. Copy your ingest token (it will look like abc123def456...).

Step 3: Instrument Your Server

Add telemetry to your MCP server with just a few lines of code:
Replace your-ingest-token-here with your actual ingest token from Step 2.

Step 4: Start Your Server

Run your instrumented MCP server as usual. Telemetry data will automatically be collected and sent to Shinzo whenever tools are executed.
Support for other capabilities like Resources, Prompts, and User Elicitation is coming soon!

Step 5: View Your Data

  1. Go to app.shinzo.ai.
  2. Navigate to the Dashboard to see real-time metrics.
  3. Check the Traces page to see individual tool executions.
  4. Visit Resources to monitor server performance.

Example: Complete MCP Server

Here’s a complete example of an instrumented MCP server:

Next Steps

Now that your server is instrumented:

TypeScript Configuration

Learn about advanced TypeScript SDK configuration options.

Python Configuration

Learn about advanced Python SDK configuration options.

Explore Dashboard

Discover all the insights available in the Shinzo Platform dashboard.

Troubleshooting

Not seeing data?

  1. Check your ingest token: Make sure it’s correct and active.
  2. Verify network access: Ensure your server can reach api.app.shinzo.ai.
  3. Check console logs: Use exporterType: "console" to check logs for anomalies.

Performance concerns?

The SDK is designed to be lightweight with minimal performance impact:
  • Telemetry is exported in batches
  • Network calls are non-blocking
  • Sampling can be configured to reduce data volume
Need help? Contact us at austin@shinzolabs.com