LogRocket

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---
name: use-logrocket
description: Investigate LogRocket session replays, user behavior, issues, recorded network requests, and product analytics through the LogRocket MCP server. Use when the user shares a LogRocket link, reports a problem in their app, wants to triage issues, asks about feature usage, or wants to check for a regression using recorded data.
---

Use the connected LogRocket MCP server. Discover the available tools and their current input schemas before calling them; the exposed tools depend on the connection's scope and toolsets.

## Select the project and time range

Infer organization and project IDs from a supplied `<organizationID>/<projectID>` App ID or LogRocket link. Otherwise use `list_organizations`, then `list_projects`. If discovery returns multiple candidates, ask which organization or project to use. A scoped connection may hide these discovery tools and omit the corresponding ID inputs; honor its scope.

Resolve relative dates using the user's current date and timezone. Include a concrete time range in queries and use ISO 8601 datetimes with offsets for structured date inputs.

`build_metric`, `get_metric`, and `use_logrocket` accept an optional IANA `timezone` that aligns time buckets to that timezone's calendar. Pass the timezone the user asks for, or otherwise the one they are working in when known. If it is unknown, omit it; a UTC offset alone does not identify a timezone. If the connection sets a default timezone, pass one only when the user asks for a different timezone. With neither, buckets align to UTC.

## Choose the tool

| Need | Tool and guidance |
| --- | --- |
| Locate sessions for a user, event, page, error, or date range | `find_sessions` with a precise natural language query. Results provide recording IDs, session IDs, session URLs, and the filters used (`metricDefinition`). Inspect those filters to check that the query matches the request. |
| Understand behavior or extract context from known sessions | `watch_sessions` with a focused query per session. Use IDs from a supplied link or returned session data, passing session IDs as integers. Sessions are analyzed independently. |
| Retrieve recorded network data | `get_network_entries`; prefer it when only network data is needed. Filter by URL, method, status, or time where useful. To investigate across sessions, find the sessions first, then query each. |
| Query a saved metric link | `get_metric` with the full `metricURL`, `startDate`, and `endDate`. This uses the saved definition. Heatmap and path analysis metrics are unsupported. |
| Run new aggregate analytics | `build_metric` with a natural language query. Check the returned metric definition, filters, grouping, and time range before interpreting the data. |
| Find and prioritize issues | `find_issues` with structured time, severity, type, and triage filters, optionally refined by a natural language query. Existing issue analyses are returned inline when available. |
| Broader investigation without a better dedicated tool | `use_logrocket` with a natural language query; include full resource URLs supplied by the user. |

If a dedicated tool is unavailable because the connection restricts toolsets, use `use_logrocket` only if exposed and suitable. Explain missing capabilities rather than inventing tools.

## Complete asynchronous work

`use_logrocket` may return `status: thinking`. Share meaningful progress, keep its `chatID`, and continue calling it with that ID and `pollForResult: true` until completion. Omit the query while polling. Reuse a completed conversation's `chatID` only for a related follow-up; omit it for a new investigation. Queries can take up to ten minutes.

`watch_sessions` returns `pendingResults` and `completedResults`. Accumulate completed results across calls. Poll with `pollForResults: true` and only the remaining fingerprints, omitting `sessions`; do not resubmit the original analyses. Continue until none remain, checking each completed result's `ok

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