/documentation/monitoring/Recent content in Monitoring & Observability on MCP Toolbox for DatabasesHugoen-us/documentation/monitoring/telemetry/Mon, 01 Jan 0001 00:00:00 +0000/documentation/monitoring/telemetry/<h2 id="about">About</h2> <p>Telemetry data such as logs, metrics, and traces will help developers understand the internal state of the system. This page walks though different types of telemetry and observability available in Toolbox.</p> <p>Toolbox exports telemetry data of logs via standard out/err, and traces/metrics through <a href="https://opentelemetry.io/">OpenTelemetry</a>. Additional flags can be passed to Toolbox to enable different logging behavior, or to export metrics through a specific <a href="/documentation/monitoring/telemetry/#exporter">exporter</a>.</p> <h2 id="logging">Logging</h2> <p>The following flags can be used to customize Toolbox logging:</p>/documentation/monitoring/export_telemetry/Mon, 01 Jan 0001 00:00:00 +0000/documentation/monitoring/export_telemetry/<h2 id="about">About</h2> <p>The <a href="https://opentelemetry.io/docs/collector/">OpenTelemetry Collector</a> offers a vendor-agnostic implementation of how to receive, process and export telemetry data. It removes the need to run, operate, and maintain multiple agents/collectors.</p> <h2 id="configure-the-collector">Configure the Collector</h2> <p>To configure the collector, you will have to provide a configuration file. The configuration file consists of four classes of pipeline component that access telemetry data.</p> <ul> <li><code>Receivers</code></li> <li><code>Processors</code></li> <li><code>Exporters</code></li> <li><code>Connectors</code></li> </ul> <p>Example of setting up the classes of pipeline components (in this example, we don&rsquo;t use connectors):</p>/documentation/monitoring/sql_commenter/Mon, 01 Jan 0001 00:00:00 +0000/documentation/monitoring/sql_commenter/<p><a href="https://google.github.io/sqlcommenter/">SQLCommenter</a> is an open-source convention that propagates application context into the database by prepending a structured comment to every SQL statement before it is executed. The comment is stripped before query planning, so it has no effect on results — but it shows up verbatim in database query logs and slow-query logs, letting you correlate a specific SQL statement back to the MCP client, LLM tool invocation, model, user, agent, and distributed trace that triggered it.</p>