OpenReplay Session Analysis MCP Server

Name: OpenReplay Session Analysis MCP Server
Author: rsp2k

@rsp2k

リポジトリ

OpenReplay Session Analysis MCP Server について

A Model Context Protocol (MCP) server for analyzing OpenReplay session recordings and user behavior patterns

#openreplay #session-analysis #user-behavior

基本情報

カテゴリ

その他

ライセンス

MIT license

ランタイム

python

トランスポート

stdio

公開者

rsp2k

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "openreplay-mcp-server": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is OpenReplay Session Analysis MCP Server?

An MCP server that enables AI assistants to analyze OpenReplay session recordings and user behavior patterns. It searches, filters, and provides actionable insights from OpenReplay data, helping developers and UX researchers detect problems and understand user journeys.

How to use OpenReplay Session Analysis MCP Server?

Install by cloning the repository, creating a Python virtual environment, and installing dependencies. Configure OpenReplay API credentials in a .env file (API key, project ID, API URL). Run the server with python run_server.py or via Docker. Connect to an MCP client like Claude Desktop by adding the server to claude_desktop_config.json.

Key features of OpenReplay Session Analysis MCP Server

Session search and filtering by date, user, errors, duration
User journey analysis with page flow mapping
Problem detection: rage clicks, form abandonment, errors
AI-powered session summaries and insights
User behavior analysis across multiple sessions
Similar session finding for comparable issues

Use cases of OpenReplay Session Analysis MCP Server

Debugging: find recent error sessions, analyze them, and discover similar issues
UX research: examine user navigation patterns and identify frustration points
Customer support: retrieve all sessions for a specific user to understand behavior
Performance analysis: detect slow-loading content and behavioral patterns

FAQ from OpenReplay Session Analysis MCP Server

What are the requirements to run this server?

You need an OpenReplay account with API access, a valid API key and project ID, network access to OpenReplay API endpoints, and Python 3.8+.

How do I configure it with Claude Desktop?

Add the server to your claude_desktop_config.json under mcpServers with the python command pointing to run_server.py and environment variables for OPENREPLAY_API_KEY and OPENREPLAY_PROJECT_ID.

What analysis tools are available?

Tools include search_sessions, get_session_details, get_user_session_history, analyze_user_journey, detect_problem_patterns, generate_session_summary, and find_similar_sessions.

Can I run the server in Docker?

Yes. Use docker-compose up with environment variables in .env, or run docker build and docker run with the appropriate environment variables.

What analysis capabilities does it offer?

It detects rage clicks, form abandonment, dead clicks, and errors; maps page flows and action breakdowns; and provides AI-generated summaries and behavioral patterns.

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