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Supported Lightrun MCP tools🔗

Lightrun MCP exposes a set of MCP tools that AI assistants can invoke to inspect and reason about live application behavior. Each tool represents a specific, production-safe debugging capability provided by Lightrun and can be accessed programmatically through the Model Context Protocol.

For an overview of Lightrun MCP concepts and architecture, see the Lightrun MCP Overview.

The following sections describe the MCP tools currently exposed by Lightrun MCP. These tools are supported starting with Lightrun version 1.75 and enable AI assistants to perform production-safe runtime inspection and debugging operations.

Discover available runtime sources🔗

Tool name: lightrun__get_runtime_sources

This tool allows you to discover which applications, services, or runtime environments are currently available for live debugging with Lightrun.

Before inspecting runtime data or capturing snapshots, you must first select the runtime source where the inspection will occur. Lightrun exposes the available runtime sources based on your permissions, such as:

  • Running applications or services also referred to Lightrun Agents.
  • Groups of instances by agent pools or by tags.
  • Custom-defined source groupings.

This step helps you identify the correct runtime target before performing live inspection or debugging actions.

Inspect runtime expression values🔗

Tool name: lightrun__get_runtime_expression_values

This tool allows you to inspect variable values and expressions as they exist during live application execution, without stopping the application or redeploying code.

Using this tool, Lightrun captures the state of your application when execution reaches a specific line of code. This makes it possible to understand how data flows through your system in real time.

Use this capability to:

  • Investigate unexpected behavior in production or staging environments.
  • Understand variable values and function arguments at specific code locations.
  • Debug issues that are difficult or impossible to reproduce locally.
  • Inspect request/response data and application state during execution.
  • Troubleshoot performance or logic issues by examining runtime values.

The values are captured non-intrusively and only when the specified code path is executed, minimizing overhead while providing precise insights.

This approach enables live debugging without code changes, redeployment, or application interruption.

Sample prompts

  • Get the runtime values of userId and orderTotal at this line.
  • Inspect the arguments passed to this function during execution.
  • Retrieve the value of transaction.amount when the transaction.approved==false is met.

Next steps🔗

Last update: January 4, 2026