OpenReplay Session Analysis MCP Server

The OpenReplay Session Analysis MCP server turns raw user‑session recordings into actionable intelligence that AI assistants can surface in real time. By exposing a rich set of tools over the Model Context Protocol, it lets developers query and analyze OpenReplay data directly from Claude or any other MCP‑compatible client. This removes the need for manual dashboards or custom API plumbing, enabling developers to embed sophisticated session‑analysis capabilities into chat flows, automated support bots, or continuous monitoring pipelines.

At its core, the server solves the problem of data friction between OpenReplay’s event streams and AI assistants. It offers a declarative interface for searching sessions, extracting detailed traces, mapping user journeys, and detecting common UX pain points such as rage clicks or form abandonment. The result is a single point of integration that translates complex analytics into concise, natural‑language insights—perfect for troubleshooting or product improvement conversations.

Key capabilities include:

• Session Search & Filtering – Advanced query parameters let you locate sessions by date range, user identity, error types, or duration.
• User Journey Analysis – The tool maps navigation paths and page flows to reveal how users traverse your application.
• Problem Detection – Automated pattern recognition flags rage clicks, form errors, and runtime exceptions.
• AI‑Powered Insights – Leveraging the underlying MCP framework, it can generate summary reports and recommendations that a human analyst would normally craft.
• Behavior Aggregation – Cross‑session analytics surface recurring patterns, helping teams spot systemic issues.
• Similar Session Discovery – By comparing session fingerprints, the server surfaces comparable problematic sessions for deeper investigation.

These features enable a range of real‑world use cases. A product manager can ask the assistant, “Show me all sessions with errors from last week,” and receive a concise list. A support engineer can request, “Generate a summary of session ABC123,” and instantly get actionable diagnostics. Continuous monitoring teams can embed the server in their alerting stacks, triggering AI‑generated explanations whenever a spike in form abandonment is detected.

Integration is straightforward: the server exposes its tools via MCP, so any client that understands the protocol can invoke them with a single JSON payload. In Claude Desktop, for example, you simply add the server to your configuration and start asking natural‑language questions. The assistant translates those queries into tool calls, receives structured results from OpenReplay, and presents them back to the user—all without leaving the chat.

What sets this MCP server apart is its end‑to‑end automation. It couples OpenReplay’s powerful session recording with an AI layer that understands context, reduces noise, and delivers clear, actionable insights. For developers building AI‑augmented workflows around user experience analysis, the OpenReplay Session Analysis MCP server offers a turnkey, extensible solution that bridges data ingestion, analytics, and conversational AI.