# Execution logs

**Execution logs** give you a way to inspect any MCP servers called by the LLM, including with their arguments and return values.&#x20;

Execution logs are useful to understand the calls being made by your agents, as well as the type of arguments. Each execution is timestamped so you can understand execution time and optimize latency accordingly.

Execution logs work out-of-the-box across any agent, so you won't have to add specific instrumentation to your code.

## Using Execution logs

Head over to [Execution logs](https://app.toolhouse.ai/execution-logs) in your Toolhouse. In the left hand side column, you will see your past executions, tagged by their own call ID as generated by the agent. Click on one execution to see its details on the right hand side of the page.

### What data is available for each execution

For each MCP server call, you'll see these details:

<table><thead><tr><th width="237">Data</th><th>Description</th></tr></thead><tbody><tr><td><strong>Call ID</strong></td><td>The ID of the call, as passed by the LLM. This is useful to tell apart two different calls of the same server by the same agent.</td></tr><tr><td><strong>Execution timestamp</strong></td><td>The date and time of when the server was called. This is computed by Toolhouse.</td></tr><tr><td><strong>Duration</strong></td><td>The duration of the exeuction. This is determined by measuring the delta between the time Toolhouse invokes the server and the time it returns its output to Toolhouse.</td></tr><tr><td><strong>Input</strong></td><td>Input arguments as generated by the LLM.</td></tr><tr><td><strong>Output</strong></td><td>The complete return value of the call.</td></tr></tbody></table>


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.toolhouse.ai/toolhouse/execution-logs.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
